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Pixis","",{"canonical":382,"robots":384},[],[],{"facebook":387,"twitter":388},{"description":382,"title":381},{"description":382,"title":381},[390],{"id":9,"type":391,"heading":392,"textBlock":9,"filterText":9,"featuredArticle":395,"formBlock":396,"logoCta":397,"user":398,"channelSelect":373},"modules_articleListing_BlockType",[393],{"text":323,"headingType":394,"headingStyle":394},"h1",[],[],[],[],[],{"articles":401},[402,439,469,500,533,564,594,625,656,686,717,748,779,809,838,868,897,927,957,986,1016,1045,1075,1104,1134,1163,1193,1222,1252,1282,1315,1344,1374,1403,1434,1464,1495,1525,1555,1584,1614,1644,1673,1703,1733,1763,1792,1822,1852,1883,1913,1942,1972,2003,2034,2065,2096,2126,2155,2185,2215,2245,2274,2304,2334,2365,2394,2423,2452,2482,2511,2540,2571,2602,2633,2663,2694,2724,2754,2785,2815,2845,2876,2906,2936,2967,2997,3028,3058,3089,3119,3150,3180,3211,3241,3271,3302,3333,3364,3394,3424,3454,3485,3515,3546,3577,3607,3638,3669,3700,3731,3761,3791],{"uri":403,"id":404,"title":405,"url":406,"postDate":407,"dateUpdated":408,"slug":409,"sectionHandle":373,"type":410,"authors":411,"seo":421,"categories":429,"contentArea":433,"siteName":371},"glossary/a-b-testing","18049","A/B Testing","https://pixis-brand-web-1dfin.sevalla.page/glossary/a-b-testing/","2025-03-13T02:42:50-04:00","2025-04-17T03:18:05-04:00","a-b-testing","glossary_Entry",[412],{"fullName":371,"asset":413,"position":419,"bio":9,"linkedIn":9,"authorPage":420},[414],{"type":27,"image":415,"mobileImage":418},[416],{"src":417,"alt":9},"https://d2pybzedimtqqo.cloudfront.net/images/Placeholders/author-placeholder.png",[],"AI Democratizer",[],{"title":422,"description":382,"advanced":423,"keywords":425,"social":426},"A/B Testing | Pixis",{"canonical":9,"robots":424},[],[],{"facebook":427,"twitter":428},{"description":382,"title":422},{"description":382,"title":422},[430],{"title":431,"slug":432},"General Marketing","general-marketing",[434],{"blocks":435},[436],{"type":437,"textBlock":438},"textBlock_Entry","\u003Cspan style=\"font-weight:400;\">A/B testing is a method that compares two different versions of a marketing element—such as a webpage, ad, or email—to determine which one performs better based on key metrics like conversions, click-through rates, or engagement. This approach helps marketers and businesses make data-backed decisions by identifying which variation yields better results from real user interactions.\u003C/span>\n\u003Ch2>\u003Cb>What You Need to Know\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A/B testing optimizes user experience and improves marketing performance. It works by dividing a sample audience into two groups, where each group is shown a different version (A or B) of the element being tested. The results are then measured to see which version performs better according to a specific goal, such as increasing sales, reducing bounce rates, or generating more clicks.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">This method is especially useful because it removes guesswork from decision-making. Instead of relying on assumptions about what will resonate with users, A/B testing provides concrete evidence based on real-world behavior. Commonly tested elements include headlines, images, calls to action, page layouts, and even colors. By continuously testing and refining their campaigns, marketers can achieve incremental improvements that lead to significant performance gains over time.\u003C/span>\n\u003Ch2>\u003Cb>How It Works\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A/B testing typically involves the following steps:\u003C/span>\n\u003Col>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Hypothesis Formation\u003C/b>\u003Cspan style=\"font-weight:400;\">: The process begins by identifying what element to test and hypothesizing how a change might improve performance. For instance, a marketer may predict that a different call-to-action phrase will increase click-through rates.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Creating Variations\u003C/b>\u003Cspan style=\"font-weight:400;\">: Two or more variations are created. For a simple A/B test, there is usually one control (original version) and one alternative version with the change.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Audience Split\u003C/b>\u003Cspan style=\"font-weight:400;\">: The audience is randomly divided into groups, with each group exposed to a different version to ensure unbiased results.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Data Collection\u003C/b>\u003Cspan style=\"font-weight:400;\">: As users interact with the test versions, data is collected on key metrics, such as the number of clicks, form submissions, or purchases.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Analysis\u003C/b>\u003Cspan style=\"font-weight:400;\">: The results are analyzed to determine which version performed better. If a significant difference is observed, the winning version is implemented.\u003C/span>\u003C/li>\n\u003C/ol>\n\u003Ch2>\u003Cb>Advantages\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A/B testing offers a range of benefits, starting with improved conversion rates. By identifying and implementing changes that positively impact user behavior, businesses can drive higher engagement and revenue. Additionally, it enhances customer experience by ensuring that the most effective elements are displayed. Testing one element at a time also provides clarity on what specifically drives improvements, eliminating confusion caused by multiple simultaneous changes.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Another advantage is reduced risk. Since changes are tested on a subset of users before full implementation, businesses can avoid costly errors and make more informed decisions. Over time, consistent testing helps companies stay competitive by continuously optimizing their digital presence.\u003C/span>\n\u003Ch2>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A/B testing is widely used across industries and digital channels. E-commerce businesses use it to optimize product pages, improving conversion rates by testing different headlines, images, and checkout processes. In email marketing, A/B testing is applied to subject lines and body content to boost open and click-through rates.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Social media platforms and advertising campaigns also benefit from A/B testing by determining which creatives, targeting strategies, and ad formats drive better engagement.\u003C/span>",{"uri":440,"id":441,"title":442,"url":443,"postDate":444,"dateUpdated":408,"slug":445,"sectionHandle":373,"type":410,"authors":446,"seo":454,"categories":462,"contentArea":464,"siteName":371},"glossary/abandoned-browse","18055","Abandoned Browse","https://pixis-brand-web-1dfin.sevalla.page/glossary/abandoned-browse/","2025-03-13T02:44:02-04:00","abandoned-browse",[447],{"fullName":371,"asset":448,"position":419,"bio":9,"linkedIn":9,"authorPage":453},[449],{"type":27,"image":450,"mobileImage":452},[451],{"src":417,"alt":9},[],[],{"title":455,"description":382,"advanced":456,"keywords":458,"social":459},"Abandoned Browse | Pixis",{"canonical":9,"robots":457},[],[],{"facebook":460,"twitter":461},{"description":382,"title":455},{"description":382,"title":455},[463],{"title":431,"slug":432},[465],{"blocks":466},[467],{"type":437,"textBlock":468},"\u003Cspan style=\"font-weight:400;\">Abandoned browse occurs when users visit a website and explore products or services but leave without taking further action, such as adding items to their shopping cart. This behavior indicates interest but can be influenced by factors like price sensitivity, insufficient product information, or a lack of urgency.\u003C/span>\n\u003Ch2>\u003Cb>What You Need to Know\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">In the online shopping journey, users often browse multiple products to compare options before making a purchase decision. However, many do not immediately proceed to checkout. Understanding abandoned browse behavior is crucial for businesses because it provides insights into how users interact with their products and services.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">There are several reasons why users might abandon a browsing session. They could be conducting research to compare prices or reading reviews. Others might be hesitant to buy due to unclear return policies or concerns about shipping costs. By analyzing browsing behavior, companies can identify patterns and develop strategies to re-engage these potential customers.\u003C/span>\n\u003Ch2>\u003Cb>How It Works\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Tracking abandoned browse behavior involves monitoring which pages and products users view during their sessions. Advanced analytics platforms and AI tools help collect this data, identifying key moments where users drop off. Businesses can then target these users with personalized marketing campaigns to reignite interest.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, after a visitor leaves a product page without adding an item to their cart, they might receive an email showcasing the same product, along with related items and social proof, such as customer reviews or ratings. Alternatively, retargeting ads may appear on social media or other websites to remind users of the products they browsed.\u003C/span>\n\u003Ch2>\u003Cb>Advantages\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Addressing abandoned browse behavior offers significant benefits, primarily through re-engagement strategies. By following up with personalized recommendations, businesses can bring potential customers back to their website, increasing the likelihood of conversion. These efforts also improve brand recall, as users are reminded of their initial interest through multiple touchpoints.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Additionally, analyzing browsing data helps businesses optimize their product pages and marketing strategies. By understanding what products attract attention but do not lead to action, companies can refine their messaging, improve product descriptions, or introduce special offers to overcome purchasing barriers.\u003C/span>\n\u003Ch2>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">E-commerce businesses commonly use retargeting and email campaigns to address abandoned browse behavior. For instance, a clothing retailer might send an email featuring products a user previously viewed, along with suggestions for complementary items. AI tools can boost these efforts by analyzing user preferences and automating follow-ups.\u003C/span>",{"uri":470,"id":471,"title":472,"url":473,"postDate":474,"dateUpdated":475,"slug":476,"sectionHandle":373,"type":410,"authors":477,"seo":485,"categories":493,"contentArea":495,"siteName":371},"glossary/abandoned-cart","18061","Abandoned Cart","https://pixis-brand-web-1dfin.sevalla.page/glossary/abandoned-cart/","2025-03-13T02:45:20-04:00","2025-04-17T03:18:06-04:00","abandoned-cart",[478],{"fullName":371,"asset":479,"position":419,"bio":9,"linkedIn":9,"authorPage":484},[480],{"type":27,"image":481,"mobileImage":483},[482],{"src":417,"alt":9},[],[],{"title":486,"description":382,"advanced":487,"keywords":489,"social":490},"Abandoned Cart | Pixis",{"canonical":9,"robots":488},[],[],{"facebook":491,"twitter":492},{"description":382,"title":486},{"description":382,"title":486},[494],{"title":431,"slug":432},[496],{"blocks":497},[498],{"type":437,"textBlock":499},"\u003Cspan style=\"font-weight:400;\">Abandoned cart refers to situations where users add items to their online shopping cart but leave the site without completing the purchase. This behavior is a major challenge for e-commerce businesses, as it represents a loss of high-intent customers who were close to converting.\u003C/span>\n\u003Ch2>\u003Cb>What You Need to Know\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Cart abandonment is often caused by factors such as unexpected costs (e.g., shipping fees), complex checkout processes, or distractions. Shoppers may also abandon carts if they are still undecided or want to continue researching alternatives. Businesses track cart abandonment to understand user behavior at this crucial stage and implement strategies to recover lost sales.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Abandoned cart strategies typically involve automated follow-ups through email or retargeting ads. These messages remind users of their incomplete purchase and often include incentives, such as discounts or free shipping, to encourage them to return and complete their order.\u003C/span>\n\u003Ch2>\u003Cb>How It Works\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Abandoned cart recovery starts by identifying users who have added items to their cart but left without checking out. Marketing automation systems then trigger follow-up emails, typically within a few hours of the cart being abandoned. These emails might feature the items left behind, personalized product recommendations, and calls to action that emphasize urgency (e.g., “Limited stock available”).\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Additionally, businesses may run retargeting campaigns on social media and other platforms to display ads reminding users of their cart contents. Advanced solutions may use AI to personalize both messaging and timing based on user behavior.\u003C/span>\n\u003Ch2>\u003Cb>Advantages\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Cart abandonment recovery efforts can significantly boost e-commerce revenue by re-engaging users who demonstrated strong purchase intent. Personalized emails have high open and click-through rates, making them an effective way to convert hesitant shoppers. Offering incentives like limited-time discounts can further increase conversion rates.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Beyond recovering lost sales, businesses gain valuable insights into common barriers that prevent users from completing purchases. By addressing these pain points—such as streamlining checkout or improving transparency around fees—companies can reduce overall abandonment rates and enhance the customer experience.\u003C/span>\n\u003Ch2>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Abandoned cart strategies are widely used in e-commerce, where automation tools make follow-up campaigns easy to deploy. For example, a beauty brand might send an email within 24 hours of a cart being abandoned, offering free shipping or highlighting product benefits to entice the shopper to return. These strategies are effective across various industries, including fashion, electronics, and subscription services.\u003C/span>",{"uri":501,"id":502,"title":503,"url":504,"postDate":505,"dateUpdated":506,"slug":507,"sectionHandle":373,"type":410,"authors":508,"seo":516,"categories":524,"contentArea":528,"siteName":371},"glossary/action-basis","17713","Action Basis","https://pixis-brand-web-1dfin.sevalla.page/glossary/action-basis/","2025-03-06T06:59:12-05:00","2025-04-17T03:17:36-04:00","action-basis",[509],{"fullName":371,"asset":510,"position":419,"bio":9,"linkedIn":9,"authorPage":515},[511],{"type":27,"image":512,"mobileImage":514},[513],{"src":417,"alt":9},[],[],{"title":517,"description":382,"advanced":518,"keywords":520,"social":521},"Action Basis | Pixis",{"canonical":9,"robots":519},[],[],{"facebook":522,"twitter":523},{"description":382,"title":517},{"description":382,"title":517},[525],{"title":526,"slug":527},"Product Nomenclature","product-nomenclature",[529],{"blocks":530},[531],{"type":437,"textBlock":532},"An Action Basis, on the Pixis AI Optimizer dashboard, is the underlying logic that explains why a Pixis AI model recommends a particular action. This action is aligned with the user’s long-term goals and objectives and is influenced by the changing parameters, goals, macro environment, and such.",{"uri":534,"id":535,"title":536,"url":537,"postDate":538,"dateUpdated":539,"slug":540,"sectionHandle":373,"type":410,"authors":541,"seo":549,"categories":557,"contentArea":559,"siteName":371},"glossary/ad-attribution","18067","Ad Attribution","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-attribution/","2025-03-13T02:46:39-04:00","2025-04-17T03:18:07-04:00","ad-attribution",[542],{"fullName":371,"asset":543,"position":419,"bio":9,"linkedIn":9,"authorPage":548},[544],{"type":27,"image":545,"mobileImage":547},[546],{"src":417,"alt":9},[],[],{"title":550,"description":382,"advanced":551,"keywords":553,"social":554},"Ad Attribution | Pixis",{"canonical":9,"robots":552},[],[],{"facebook":555,"twitter":556},{"description":382,"title":550},{"description":382,"title":550},[558],{"title":431,"slug":432},[560],{"blocks":561},[562],{"type":437,"textBlock":563},"\u003Cspan style=\"font-weight:400;\">Ad attribution is the process of identifying which marketing channels and campaigns drive consumer actions, such as purchases or sign-ups. It helps businesses understand which ads contribute to conversions and how customers interact with different touchpoints before making a decision.\u003C/span>\n\u003Ch2>\u003Cb>What You Should Know\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">In a multi-channel marketing environment, customers often interact with multiple ads before converting. For example, a customer might first see a shoe ad on Instagram, then receive an email promotion, and finally click a Google ad before purchasing. Ad attribution assigns credit to one or more of these touchpoints, helping businesses measure the impact of each ad.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Common attribution models include:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>First-click attribution:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Gives credit to the first ad the customer interacted with.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Last-click attribution:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Credits the last ad before conversion.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Linear attribution:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Distributes credit evenly across all touchpoints.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Multi-touch attribution:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Evaluates the impact of each interaction in the customer journey.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Ch2>\u003Cb>How It Works\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Ad attribution relies on tracking technologies such as cookies, UTM parameters, and pixels. Marketing platforms collect data on clicks, impressions, and conversions, then apply attribution models to analyze performance. Businesses use these insights to adjust ad spend, refine targeting, and improve messaging.\u003C/span>\n\u003Ch2>\u003Cb>Advantages\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Ad attribution helps businesses allocate their marketing budget effectively by identifying the highest-performing channels. It also improves return on investment (ROI) by highlighting which ads generate conversions. Additionally, attribution insights reveal how different platforms work together to drive customer actions, supporting better campaign integration.\u003C/span>\n\u003Ch2>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A clothing brand running ads on Instagram, TikTok, and Google Shopping can use attribution models to determine which platform drives the most sales. A food delivery app can track which ads convert users who download their app versus those who make a purchase.\u003C/span>",{"uri":565,"id":566,"title":567,"url":568,"postDate":569,"dateUpdated":539,"slug":570,"sectionHandle":373,"type":410,"authors":571,"seo":579,"categories":587,"contentArea":589,"siteName":371},"glossary/ad-delivery-optimization","18073","Ad Delivery Optimization","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-delivery-optimization/","2025-03-13T02:48:36-04:00","ad-delivery-optimization",[572],{"fullName":371,"asset":573,"position":419,"bio":9,"linkedIn":9,"authorPage":578},[574],{"type":27,"image":575,"mobileImage":577},[576],{"src":417,"alt":9},[],[],{"title":580,"description":382,"advanced":581,"keywords":583,"social":584},"Ad Delivery Optimization | Pixis",{"canonical":9,"robots":582},[],[],{"facebook":585,"twitter":586},{"description":382,"title":580},{"description":382,"title":580},[588],{"title":431,"slug":432},[590],{"blocks":591},[592],{"type":437,"textBlock":593},"\u003Cspan style=\"font-weight:400;\">Ad delivery optimization is the process of using algorithms and machine learning to serve ads to the people most likely to take a desired action, such as purchasing a product or downloading an app. Platforms like Facebook Ads and Google Ads automatically adjust ad placements, audiences, and bidding strategies to maximize results.\u003C/span>\n\u003Ch2>\u003Cb>What You Should Know\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Ad delivery optimization goes beyond showing ads to a broad audience. It uses behavioral data to identify users who are most likely to convert. For instance, if a fitness brand runs ads for workout apparel, the platform might prioritize showing ads to people who have previously interacted with fitness content.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Different optimization objectives include:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Conversions:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Targets users likely to complete purchases or sign-ups.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Clicks:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Focuses on driving traffic to a website.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Reach:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Maximizes the number of unique people who see the ad.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Engagement:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Targets users likely to interact with likes, shares, or comments.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Ch2>\u003Cb>How It Works\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Ad platforms analyze user data, including past behavior and demographics. Machine learning models predict which users are most likely to engage with the ad. The platform then adjusts placements and bid amounts to reach these users effectively. For example, Facebook may deliver a clothing ad to users who recently browsed similar products or interacted with fashion influencers.\u003C/span>\n\u003Ch2>\u003Cb>Advantages\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Ad delivery optimization reduces wasted ad spend by focusing on users most likely to convert. It improves campaign performance by leveraging real-time insights to refine targeting. Additionally, automated optimization saves time, allowing businesses to focus on creative and strategy rather than manual adjustments.\u003C/span>\n\u003Ch2>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A streaming service promoting a new series may optimize for video views to reach users who frequently watch trailers. An online shoe retailer running a flash sale may optimize for conversions to ensure the ads reach people ready to purchase.\u003C/span>",{"uri":595,"id":596,"title":597,"url":598,"postDate":599,"dateUpdated":600,"slug":601,"sectionHandle":373,"type":410,"authors":602,"seo":610,"categories":618,"contentArea":620,"siteName":371},"glossary/ad-effectiveness","18079","Ad Effectiveness","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-effectiveness/","2025-03-13T02:50:57-04:00","2025-04-17T03:18:08-04:00","ad-effectiveness",[603],{"fullName":371,"asset":604,"position":419,"bio":9,"linkedIn":9,"authorPage":609},[605],{"type":27,"image":606,"mobileImage":608},[607],{"src":417,"alt":9},[],[],{"title":611,"description":382,"advanced":612,"keywords":614,"social":615},"Ad Effectiveness | Pixis",{"canonical":9,"robots":613},[],[],{"facebook":616,"twitter":617},{"description":382,"title":611},{"description":382,"title":611},[619],{"title":431,"slug":432},[621],{"blocks":622},[623],{"type":437,"textBlock":624},"\u003Cspan style=\"font-weight:400;\">Ad effectiveness measures how well an advertisement achieves its intended goals, such as increasing brand awareness, driving sales, or engaging an audience. It evaluates whether an ad successfully influences consumer behavior.\u003C/span>\n\u003Ch2>\u003Cb>What You Should Know\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Ad effectiveness is assessed using key performance indicators (KPIs) like click-through rate (CTR), conversion rate, and return on ad spend (ROAS). However, effectiveness goes beyond numbers, measuring how well an ad resonates emotionally and influences decision-making.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, a travel brand may launch a video ad showcasing tropical destinations. Effectiveness is measured by video engagement metrics, website visits, and bookings generated from the campaign.\u003C/span>\n\u003Ch2>\u003Cb>How It Works\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Businesses measure ad effectiveness through a combination of direct metrics (clicks, sales) and indirect metrics (brand recall, sentiment analysis). A/B testing helps compare different ad versions to see which drives better results. Surveys and brand lift studies assess whether the ad improves customer perception.\u003C/span>\n\u003Ch2>\u003Cb>Advantages\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Measuring ad effectiveness allows businesses to identify which campaigns drive the highest return on investment. It also provides insights into audience preferences, guiding future creative strategies. Additionally, effective ads improve brand recognition and customer loyalty.\u003C/span>\n\u003Ch2>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A beverage company launching a summer campaign may measure ad effectiveness by tracking in-store sales and social media engagement. A fashion brand running influencer ads may measure effectiveness through follower growth and website traffic. Ad effectiveness metrics guide businesses in refining their marketing strategies.\u003C/span>",{"uri":626,"id":627,"title":628,"url":629,"postDate":630,"dateUpdated":631,"slug":632,"sectionHandle":373,"type":410,"authors":633,"seo":641,"categories":649,"contentArea":651,"siteName":371},"glossary/ad-exchange","18085","Ad Exchange","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-exchange/","2025-03-13T02:51:53-04:00","2025-04-17T03:18:09-04:00","ad-exchange",[634],{"fullName":371,"asset":635,"position":419,"bio":9,"linkedIn":9,"authorPage":640},[636],{"type":27,"image":637,"mobileImage":639},[638],{"src":417,"alt":9},[],[],{"title":642,"description":382,"advanced":643,"keywords":645,"social":646},"Ad Exchange | Pixis",{"canonical":9,"robots":644},[],[],{"facebook":647,"twitter":648},{"description":382,"title":642},{"description":382,"title":642},[650],{"title":431,"slug":432},[652],{"blocks":653},[654],{"type":437,"textBlock":655},"\u003Cspan style=\"font-weight:400;\">An ad exchange is a digital marketplace where advertisers and publishers buy and sell ad space in real time. It facilitates automated transactions using real-time bidding (RTB) to place ads on websites, apps, and videos.\u003C/span>\n\u003Ch2>\u003Cb>What You Should Know\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Ad exchanges connect advertisers seeking to display their ads with publishers offering digital space. Unlike direct deals with publishers, ad exchanges allow advertisers to reach a wide audience by bidding on available impressions in milliseconds. For example, when a user visits a news website, an ad exchange auctions the space to advertisers, and the highest bidder’s ad appears instantly.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Popular ad exchanges include Google Ad Exchange and OpenX.\u003C/span>\n\u003Ch2>\u003Cb>How It Works\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">When a user visits a website, the publisher’s ad inventory becomes available on the ad exchange. Advertisers bid in real time through demand-side platforms (DSPs). The ad exchange matches bids with inventory and displays the winning ad. This process, known as real-time bidding (RTB), occurs in milliseconds.\u003C/span>\n\u003Ch2>\u003Cb>Advantages\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Ad exchanges increase efficiency by automating ad buying and expanding reach across multiple publishers. They provide transparent pricing and performance metrics, helping advertisers track ROI. Additionally, ad exchanges allow precise targeting by offering data-driven audience segmentation.\u003C/span>\n\u003Ch2>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A sneaker brand may use an ad exchange to display ads on sports blogs, lifestyle websites, and fitness apps. A cosmetics company could bid for video ad space across beauty YouTube channels.\u003C/span>",{"uri":657,"id":658,"title":659,"url":660,"postDate":661,"dateUpdated":631,"slug":662,"sectionHandle":373,"type":410,"authors":663,"seo":671,"categories":679,"contentArea":681,"siteName":371},"glossary/ad-fatigue","18091","Ad Fatigue","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-fatigue/","2025-03-13T02:53:04-04:00","ad-fatigue",[664],{"fullName":371,"asset":665,"position":419,"bio":9,"linkedIn":9,"authorPage":670},[666],{"type":27,"image":667,"mobileImage":669},[668],{"src":417,"alt":9},[],[],{"title":672,"description":382,"advanced":673,"keywords":675,"social":676},"Ad Fatigue | Pixis",{"canonical":9,"robots":674},[],[],{"facebook":677,"twitter":678},{"description":382,"title":672},{"description":382,"title":672},[680],{"title":431,"slug":432},[682],{"blocks":683},[684],{"type":437,"textBlock":685},"\u003Cspan style=\"font-weight:400;\">Ad fatigue occurs when consumers see the same advertisement too frequently, causing them to lose interest and engagement. As ad fatigue sets in, metrics like click-through rate (CTR) decline, and campaign performance suffers.\u003C/span>\n\u003Ch2>\u003Cb>What You Should Know\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Repeated exposure to the same ad can annoy audiences and reduce effectiveness. For example, if a user sees the same ad for a coffee brand multiple times on Instagram within a day, they may start ignoring it or hiding the ad. This results in wasted ad spend and lower campaign performance.\u003C/span>\n\u003Ch2>\u003Cb>How It Works\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Platforms like Facebook and Google Ads track ad frequency, which measures how often users see an ad. When performance drops as frequency increases, ad fatigue is likely. To combat fatigue, advertisers rotate ad creatives, change messaging, or adjust targeting strategies.\u003C/span>\n\u003Ch2>\u003Cb>Advantages\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Managing ad fatigue improves engagement rates and prevents users from becoming annoyed with the brand. It also helps maintain a strong return on investment (ROI) by keeping ads fresh and relevant. Addressing fatigue early ensures that campaigns remain effective over time.\u003C/span>\n\u003Ch2>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A beauty brand running holiday ads may use multiple creative versions, such as video tutorials and carousel ads, to prevent fatigue. A streaming service may switch between trailers and cast interviews to maintain user interest. Managing ad fatigue is critical for long-term campaign success.\u003C/span>",{"uri":687,"id":688,"title":689,"url":690,"postDate":691,"dateUpdated":692,"slug":693,"sectionHandle":373,"type":410,"authors":694,"seo":702,"categories":710,"contentArea":712,"siteName":371},"glossary/ad-frequency","18097","Ad Frequency","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-frequency/","2025-03-13T02:54:43-04:00","2025-04-17T03:18:10-04:00","ad-frequency",[695],{"fullName":371,"asset":696,"position":419,"bio":9,"linkedIn":9,"authorPage":701},[697],{"type":27,"image":698,"mobileImage":700},[699],{"src":417,"alt":9},[],[],{"title":703,"description":382,"advanced":704,"keywords":706,"social":707},"Ad Frequency | Pixis",{"canonical":9,"robots":705},[],[],{"facebook":708,"twitter":709},{"description":382,"title":703},{"description":382,"title":703},[711],{"title":431,"slug":432},[713],{"blocks":714},[715],{"type":437,"textBlock":716},"\u003Cspan style=\"font-weight:400;\">Ad frequency measures how often the same user sees an ad within a specific time period. It is a key metric for managing campaign reach and effectiveness. Frequency is calculated by dividing total impressions by unique users.\u003C/span>\n\u003Ch2>\u003Cb>What You Should Know\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">The right ad frequency ensures that users remember the brand without feeling overwhelmed. For example, seeing an ad for a new smartphone two or three times may encourage interest, while seeing it ten times in a day could cause annoyance. Finding the optimal frequency depends on the platform, audience, and campaign objective.\u003C/span>\n\u003Ch2>\u003Cb>How It Works\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Ad platforms track impressions and unique views to calculate frequency. Advertisers set frequency caps to limit how many times a user sees the ad. For example, a retail brand may cap frequency at three impressions per week to maintain engagement without causing fatigue.\u003C/span>\n\u003Ch2>\u003Cb>Advantages\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Optimizing ad frequency improves brand recall while minimizing ad fatigue. Balanced frequency ensures that ad spend reaches a broad audience rather than repeatedly targeting the same users. Proper frequency management also contributes to a positive brand image by avoiding overexposure.\u003C/span>\n\u003Ch2>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A fast-food chain promoting a limited-time offer may aim for moderate frequency to drive urgency without overwhelming users. A fashion retailer launching a new collection may use higher frequency initially to build awareness, then taper off as the campaign matures.\u003C/span>",{"uri":718,"id":719,"title":720,"url":721,"postDate":722,"dateUpdated":723,"slug":724,"sectionHandle":373,"type":410,"authors":725,"seo":733,"categories":741,"contentArea":743,"siteName":371},"glossary/ad-impression","18103","Ad Impression","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-impression/","2025-03-13T02:55:52-04:00","2025-04-17T03:18:11-04:00","ad-impression",[726],{"fullName":371,"asset":727,"position":419,"bio":9,"linkedIn":9,"authorPage":732},[728],{"type":27,"image":729,"mobileImage":731},[730],{"src":417,"alt":9},[],[],{"title":734,"description":382,"advanced":735,"keywords":737,"social":738},"Ad Impression | Pixis",{"canonical":9,"robots":736},[],[],{"facebook":739,"twitter":740},{"description":382,"title":734},{"description":382,"title":734},[742],{"title":431,"slug":432},[744],{"blocks":745},[746],{"type":437,"textBlock":747},"\u003Cspan style=\"font-weight:400;\">An ad impression refers to the number of times an advertisement is displayed on a screen, regardless of whether the user interacts with it. Impressions measure ad visibility rather than engagement, making them a key metric for brand awareness campaigns.\u003C/span>\n\u003Ch2>\u003Cb>What You Should Know\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Ad impressions are counted every time an ad is loaded and shown to a user. For example, if a user scrolls through Instagram and sees a shoe ad three times in their feed, it counts as three impressions. Impressions do not indicate clicks or actions; they measure exposure.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">There are two common types of impressions:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Served Impressions:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Counted when the ad server delivers the ad to the publisher’s site.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Viewable Impressions:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Counted only when the ad meets viewability standards, such as appearing at least 50% on the screen for one second (as defined by the Media Rating Council).\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Ch2>\u003Cb>How It Works\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">Advertising platforms like Google Ads, Facebook Ads, and display networks track impressions automatically. Advertisers often purchase impressions through cost-per-thousand-impressions (CPM) bidding, paying for every 1,000 times the ad is shown.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Marketers use impression data to evaluate ad reach and adjust strategies to increase visibility. For example, a fashion brand launching a new collection may aim for high impressions on Instagram to boost awareness before a sale.\u003C/span>\n\u003Ch2>\u003Cb>Advantages\u003C/b>\u003C/h2>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Boosts Brand Awareness:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Repeated impressions reinforce brand messaging, especially for new products.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Measures Campaign Reach:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Provides insights into how many people are exposed to an ad.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Informs Frequency Management:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Helps advertisers identify if users are seeing ads too often or not enough.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Ch2>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h2>\n\u003Cspan style=\"font-weight:400;\">A cosmetics brand promoting a new lipstick line tracks impressions from Instagram Stories and TikTok ads to measure reach. A streaming service launching a new series uses impressions to gauge how many users see their trailer on YouTube and connected TV platforms.\u003C/span>",{"uri":749,"id":750,"title":751,"url":752,"postDate":753,"dateUpdated":754,"slug":755,"sectionHandle":373,"type":410,"authors":756,"seo":764,"categories":772,"contentArea":774,"siteName":371},"glossary/ad-inventory","17563","Ad Inventory","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-inventory/","2025-04-17T03:17:00-04:00","2025-04-17T03:17:23-04:00","ad-inventory",[757],{"fullName":371,"asset":758,"position":419,"bio":9,"linkedIn":9,"authorPage":763},[759],{"type":27,"image":760,"mobileImage":762},[761],{"src":417,"alt":9},[],[],{"title":765,"description":382,"advanced":766,"keywords":768,"social":769},"Ad Inventory | Pixis",{"canonical":9,"robots":767},[],[],{"facebook":770,"twitter":771},{"description":382,"title":765},{"description":382,"title":765},[773],{"title":526,"slug":527},[775],{"blocks":776},[777],{"type":437,"textBlock":778},"\u003Cspan style=\"font-weight:400;\">Ad inventory refers to the total amount of advertising space available for sale on a website, app, or digital platform. Publishers offer this space to advertisers through direct sales or programmatic advertising platforms.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Every digital platform with ads, from social media to blogs, has a finite amount of space to display ads. Ad inventory can include banner ads, sponsored posts, and video pre-rolls. Platforms categorize inventory based on factors such as audience demographics, page placement, and ad format.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Inventory is typically sold through:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Direct Sales:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Deals between advertisers and publishers.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Programmatic Auctions:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Real-time bidding (RTB) through ad exchanges and demand-side platforms (DSPs).\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Publishers define available inventory and set prices, either per impression (CPM) or per click (CPC). When users visit a website, the ad server fills available inventory with ads purchased through direct sales or programmatic auctions.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, a food blog may offer inventory for banner ads and sponsored recipe videos. Advertisers bid for these spaces, and the highest bidder’s ad appears when readers visit the site.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Expands Ad Reach:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Provides advertisers with access to diverse audiences across multiple platforms.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Flexible Pricing Models:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Offers options like CPM or CPC to suit different campaign goals.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Optimizes Revenue for Publishers:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Helps publishers monetize their content effectively.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">A travel agency purchases ad inventory on popular travel blogs and YouTube travel channels to promote vacation packages. A sports apparel brand buys inventory on ESPN’s mobile app to reach fans during live game streams.\u003C/span>",{"uri":780,"id":781,"title":782,"url":783,"postDate":753,"dateUpdated":784,"slug":785,"sectionHandle":373,"type":410,"authors":786,"seo":794,"categories":802,"contentArea":804,"siteName":371},"glossary/ad-network","17569","Ad Network","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-network/","2025-04-17T03:17:24-04:00","ad-network",[787],{"fullName":371,"asset":788,"position":419,"bio":9,"linkedIn":9,"authorPage":793},[789],{"type":27,"image":790,"mobileImage":792},[791],{"src":417,"alt":9},[],[],{"title":795,"description":382,"advanced":796,"keywords":798,"social":799},"Ad Network | Pixis",{"canonical":9,"robots":797},[],[],{"facebook":800,"twitter":801},{"description":382,"title":795},{"description":382,"title":795},[803],{"title":526,"slug":527},[805],{"blocks":806},[807],{"type":437,"textBlock":808},"\u003Cspan style=\"font-weight:400;\">An ad network is a platform that connects advertisers with publishers by aggregating available ad inventory and facilitating ad placements across multiple websites and apps.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Ad networks simplify the digital advertising process by collecting inventory from numerous publishers and offering it to advertisers. They categorize inventory by factors like audience demographics, content type, and geographic location, allowing advertisers to reach specific audiences without negotiating with individual publishers.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">There are different types of ad networks:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Vertical Networks:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Focus on specific industries or niches, such as fashion or travel.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Premium Networks:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Offer inventory from high-quality, reputable publishers.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Blind Networks:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Provide large-scale reach without disclosing specific publisher details.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Ad networks use automated platforms to match ads with suitable inventory. Advertisers set their targeting preferences and budgets, and the network distributes ads across relevant sites. The ad network handles tracking, reporting, and optimization.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, a fitness brand using a display ad network can reach audiences on health blogs, YouTube fitness channels, and mobile workout apps through a single campaign.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Scalability:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Allows advertisers to reach large audiences quickly.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Efficiency:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Reduces the time spent negotiating with individual publishers.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Targeting Capabilities:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Offers audience segmentation based on behavior, interests, and location.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">A shoe brand uses the Google Display Network to promote a new sneaker line across blogs, shopping sites, and mobile apps. A streaming service partners with a premium video ad network to run trailers before popular video content on entertainment websites.\u003C/span>",{"uri":810,"id":811,"title":812,"url":813,"postDate":753,"dateUpdated":784,"slug":814,"sectionHandle":373,"type":410,"authors":815,"seo":823,"categories":831,"contentArea":833,"siteName":371},"glossary/ad-placement","17575","Ad Placement","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-placement/","ad-placement",[816],{"fullName":371,"asset":817,"position":419,"bio":9,"linkedIn":9,"authorPage":822},[818],{"type":27,"image":819,"mobileImage":821},[820],{"src":417,"alt":9},[],[],{"title":824,"description":382,"advanced":825,"keywords":827,"social":828},"Ad Placement | Pixis",{"canonical":9,"robots":826},[],[],{"facebook":829,"twitter":830},{"description":382,"title":824},{"description":382,"title":824},[832],{"title":526,"slug":527},[834],{"blocks":835},[836],{"type":437,"textBlock":837},"\u003Cspan style=\"font-weight:400;\">Ad placement refers to the specific locations where an ad appears on a digital platform, such as websites, apps, or social media feeds. It determines how and where audiences see ads, influencing engagement and performance.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Ad placements include a variety of formats, such as:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>In-Feed Ads:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Appear in social media feeds (e.g., Instagram, TikTok).\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Banner Ads:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Display at the top, bottom, or sides of websites.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Pre-Roll Video Ads:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Play before video content on platforms like YouTube.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Sponsored Content:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Integrated into website articles or blog posts.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Platforms often allow advertisers to choose between:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Automatic Placements:\u003C/b>\u003Cspan style=\"font-weight:400;\"> The platform distributes ads based on performance potential.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Manual Placements:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Advertisers select specific platforms or positions.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Ad placement is managed through ad platforms like Meta Ads Manager or Google Ads. Advertisers select their audience, budget, and placement preferences. Algorithms then determine the most effective locations for the ads based on the campaign objectives.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, a fashion brand may choose Instagram Stories and TikTok videos for a visually driven campaign targeting younger audiences.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Maximizes Visibility:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Effective placement ensures ads reach audiences in high-traffic areas.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Improves Relevance:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Matching ad formats to platform preferences increases engagement.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Optimizes Performance:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Platforms use algorithms to place ads where they are likely to perform best.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">A cosmetics brand chooses Instagram Reels and Pinterest boards to promote new makeup products. A local restaurant runs ads on Google Maps placements to reach users searching for nearby dining options.\u003C/span>\n\n ",{"uri":839,"id":840,"title":841,"url":842,"postDate":753,"dateUpdated":843,"slug":844,"sectionHandle":373,"type":410,"authors":845,"seo":853,"categories":861,"contentArea":863,"siteName":371},"glossary/ad-quality-score","17581","Ad Quality Score","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-quality-score/","2025-04-17T03:17:25-04:00","ad-quality-score",[846],{"fullName":371,"asset":847,"position":419,"bio":9,"linkedIn":9,"authorPage":852},[848],{"type":27,"image":849,"mobileImage":851},[850],{"src":417,"alt":9},[],[],{"title":854,"description":382,"advanced":855,"keywords":857,"social":858},"Ad Quality Score | Pixis",{"canonical":9,"robots":856},[],[],{"facebook":859,"twitter":860},{"description":382,"title":854},{"description":382,"title":854},[862],{"title":526,"slug":527},[864],{"blocks":865},[866],{"type":437,"textBlock":867},"\u003Cspan style=\"font-weight:400;\">Ad Quality Score is a metric used by platforms like Google Ads to evaluate the relevance and quality of an advertisement. It impacts ad placement and cost-per-click (CPC), making it a crucial factor for campaign success.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Quality Score is typically calculated based on:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Expected Click-Through Rate (CTR):\u003C/b>\u003Cspan style=\"font-weight:400;\"> The likelihood that users will click the ad.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Ad Relevance:\u003C/b>\u003Cspan style=\"font-weight:400;\"> How closely the ad matches user search queries or interests.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Landing Page Experience:\u003C/b>\u003Cspan style=\"font-weight:400;\"> The relevance and usability of the page users visit after clicking the ad.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Scores range from 1 to 10, with higher scores indicating better ad quality and lower costs.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Platforms analyze user behavior and feedback to assign a score. Ads with high relevance and strong landing page experiences earn higher scores. A high score can lower CPC and improve ad placement in search results.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, a sportswear brand running Google Ads for “running shoes” will score higher if the ad leads to a dedicated landing page featuring running shoes rather than a generic homepage.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Reduces Advertising Costs:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Higher scores lower the cost-per-click.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Improves Ad Placement:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Quality ads appear more prominently in search results or feeds.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Boosts Campaign Effectiveness:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Relevance leads to higher engagement rates.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">A pet supply store optimizes landing pages to improve Quality Score for ads targeting “organic dog food.” A fashion brand refines ad copy to match trending search terms like “summer dresses 2024” to increase relevance and CTR.\u003C/span>",{"uri":869,"id":870,"title":871,"url":872,"postDate":753,"dateUpdated":843,"slug":873,"sectionHandle":373,"type":410,"authors":874,"seo":882,"categories":890,"contentArea":892,"siteName":371},"glossary/ad-rank","17587","Ad Rank","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-rank/","ad-rank",[875],{"fullName":371,"asset":876,"position":419,"bio":9,"linkedIn":9,"authorPage":881},[877],{"type":27,"image":878,"mobileImage":880},[879],{"src":417,"alt":9},[],[],{"title":883,"description":382,"advanced":884,"keywords":886,"social":887},"Ad Rank | Pixis",{"canonical":9,"robots":885},[],[],{"facebook":888,"twitter":889},{"description":382,"title":883},{"description":382,"title":883},[891],{"title":526,"slug":527},[893],{"blocks":894},[895],{"type":437,"textBlock":896},"\u003Cspan style=\"font-weight:400;\">Ad Rank determines the position of an ad on a search engine results page (SERP) or within a display network. It is a key factor in how prominently ads appear and is calculated based on bid amount, ad quality, and expected impact of ad extensions.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Ad Rank is influenced by:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Bid Amount:\u003C/b>\u003Cspan style=\"font-weight:400;\"> The maximum amount an advertiser is willing to pay per click.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Ad Quality:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Includes Quality Score factors such as relevance and landing page experience.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Expected Impact of Extensions:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Additional information like sitelinks or call buttons can improve rank.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">High Ad Rank increases the likelihood that an ad appears in premium positions, such as the top of search results.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Search engines calculate Ad Rank for every eligible ad in real time during a search. Ads with higher ranks win better placements. For example, a sneaker brand bidding on “running shoes” may rank higher than competitors if it has a well-optimized ad and landing page.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Improves Visibility:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Higher-ranked ads appear in prime locations.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Increases Click Potential:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Ads in top positions often receive more clicks.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Rewards Quality:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Better ad experiences can outrank competitors, even with lower bids.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">A skincare brand running Google Ads for “moisturizing cream” optimizes its landing page to improve Ad Rank. A food delivery service uses ad extensions with “Order Now” buttons to increase its rank on mobile searches.\u003C/span>",{"uri":898,"id":899,"title":900,"url":901,"postDate":753,"dateUpdated":902,"slug":903,"sectionHandle":373,"type":410,"authors":904,"seo":912,"categories":920,"contentArea":922,"siteName":371},"glossary/ad-recall","17593","Ad Recall","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-recall/","2025-04-17T03:17:26-04:00","ad-recall",[905],{"fullName":371,"asset":906,"position":419,"bio":9,"linkedIn":9,"authorPage":911},[907],{"type":27,"image":908,"mobileImage":910},[909],{"src":417,"alt":9},[],[],{"title":913,"description":382,"advanced":914,"keywords":916,"social":917},"Ad Recall | Pixis",{"canonical":9,"robots":915},[],[],{"facebook":918,"twitter":919},{"description":382,"title":913},{"description":382,"title":913},[921],{"title":526,"slug":527},[923],{"blocks":924},[925],{"type":437,"textBlock":926},"\u003Cspan style=\"font-weight:400;\">Ad recall measures how well audiences remember an advertisement after seeing it. It is a key indicator of brand awareness and ad effectiveness, especially for visual and video campaigns.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Ad recall assesses how likely users are to remember an ad within a set period, such as two days. Platforms like Meta Ads Manager estimate ad recall based on engagement patterns and campaign reach. For example, a user who watches a 15-second video ad for a coffee brand may recall the ad when asked if they’ve seen a coffee promotion recently.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">There are two types of ad recall:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Aided Recall:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Measures recognition when users are shown the ad or brand name.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Unaided Recall:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Measures recall without prompting.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Platforms track engagement, such as video views or social interactions, and estimate how memorable an ad is based on user behavior. Post-campaign surveys or brand lift studies can provide additional insights.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Measures Brand Impact:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Provides insight into ad memorability.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Evaluates Creative Effectiveness:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Helps assess if visuals, slogans, or music stick with audiences.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Supports Campaign Optimization:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Guides adjustments to increase engagement.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">A soft drink brand uses ad recall lift surveys to measure the impact of its TikTok ad campaign. A beauty brand tracks ad recall from Instagram Stories ads to assess how memorable a new product launch was.\u003C/span>",{"uri":928,"id":929,"title":930,"url":931,"postDate":753,"dateUpdated":932,"slug":933,"sectionHandle":373,"type":410,"authors":934,"seo":942,"categories":950,"contentArea":952,"siteName":371},"glossary/ad-relevance-score","17599","Ad Relevance Score","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-relevance-score/","2025-04-17T03:17:27-04:00","ad-relevance-score",[935],{"fullName":371,"asset":936,"position":419,"bio":9,"linkedIn":9,"authorPage":941},[937],{"type":27,"image":938,"mobileImage":940},[939],{"src":417,"alt":9},[],[],{"title":943,"description":382,"advanced":944,"keywords":946,"social":947},"Ad Relevance Score | Pixis",{"canonical":9,"robots":945},[],[],{"facebook":948,"twitter":949},{"description":382,"title":943},{"description":382,"title":943},[951],{"title":526,"slug":527},[953],{"blocks":954},[955],{"type":437,"textBlock":956},"\u003Cspan style=\"font-weight:400;\">Ad relevance score measures how closely an ad matches its target audience’s interests and behaviors. Platforms like Meta and Google assign this score based on engagement metrics and feedback.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Ad relevance score is influenced by factors such as:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Positive Interactions:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Clicks, likes, shares, and comments.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Negative Feedback:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Ad hides or reports from users.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Alignment with Target Audience:\u003C/b>\u003Cspan style=\"font-weight:400;\"> How well the ad matches audience preferences and search intent.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Scores typically range from 1 to 10, with higher scores indicating better audience alignment and lower advertising costs.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Platforms analyze engagement patterns to assign a relevance score. Ads with high scores are more likely to appear in competitive placements at lower costs. For example, a sneaker brand targeting runners will earn a higher score if its ads highlight performance benefits rather than generic shoe styles.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Reduces Ad Costs:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Higher relevance leads to lower cost-per-click (CPC).\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Improves Audience Targeting:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Ensures ads reach users most likely to engage.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Boosts Campaign Performance:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Relevance often correlates with higher conversion rates.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">A coffee brand adjusts its Facebook ad copy to highlight “morning energy” based on user feedback, raising its relevance score. A clothing retailer uses interest-based targeting on Instagram to promote winter coats to users browsing cold-weather fashion trends.\u003C/span>\n\n ",{"uri":958,"id":959,"title":960,"url":961,"postDate":753,"dateUpdated":932,"slug":962,"sectionHandle":373,"type":410,"authors":963,"seo":971,"categories":979,"contentArea":981,"siteName":371},"glossary/ad-revenue","17605","Ad Revenue","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-revenue/","ad-revenue",[964],{"fullName":371,"asset":965,"position":419,"bio":9,"linkedIn":9,"authorPage":970},[966],{"type":27,"image":967,"mobileImage":969},[968],{"src":417,"alt":9},[],[],{"title":972,"description":382,"advanced":973,"keywords":975,"social":976},"Ad Revenue | Pixis",{"canonical":9,"robots":974},[],[],{"facebook":977,"twitter":978},{"description":382,"title":972},{"description":382,"title":972},[980],{"title":526,"slug":527},[982],{"blocks":983},[984],{"type":437,"textBlock":985},"\u003Cspan style=\"font-weight:400;\">Ad revenue is the income generated from displaying advertisements on digital platforms such as websites, apps, and social media channels. It is a primary source of revenue for publishers, influencers, and content creators.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Ad revenue is typically earned through models such as:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Cost-Per-Click (CPC):\u003C/b>\u003Cspan style=\"font-weight:400;\"> Advertisers pay when users click on their ads.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Cost-Per-Thousand Impressions (CPM):\u003C/b>\u003Cspan style=\"font-weight:400;\"> Advertisers pay for every 1,000 ad views.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Cost-Per-Action (CPA):\u003C/b>\u003Cspan style=\"font-weight:400;\"> Payment occurs when users complete a specific action, such as making a purchase.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Platforms like Google AdSense, YouTube, and TikTok Creator Fund distribute revenue based on performance metrics and audience engagement.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Ad servers place ads on websites or apps based on targeting parameters. Revenue is generated when users interact with or view these ads. Programmatic platforms use real-time bidding (RTB) to maximize revenue by selling ad space to the highest bidder. For example, a food blog running banner ads through Google AdSense earns a share of the revenue each time readers view or click on the ads.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Monetizes Free Content:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Provides income without charging users for access.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Scalable Revenue Stream:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Earnings increase with traffic growth.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Supports Content Creation:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Funds creators and publishers to continue producing valuable content.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A parenting blog uses display ads through Google AdSense to generate income from high-traffic articles. A gaming app integrates rewarded video ads, earning revenue when users watch ads in exchange for in-game rewards.\u003C/span>\n\n ",{"uri":987,"id":988,"title":989,"url":990,"postDate":753,"dateUpdated":991,"slug":992,"sectionHandle":373,"type":410,"authors":993,"seo":1001,"categories":1009,"contentArea":1011,"siteName":371},"glossary/ad-rotation","17611","Ad Rotation","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-rotation/","2025-04-17T03:17:28-04:00","ad-rotation",[994],{"fullName":371,"asset":995,"position":419,"bio":9,"linkedIn":9,"authorPage":1000},[996],{"type":27,"image":997,"mobileImage":999},[998],{"src":417,"alt":9},[],[],{"title":1002,"description":382,"advanced":1003,"keywords":1005,"social":1006},"Ad Rotation | Pixis",{"canonical":9,"robots":1004},[],[],{"facebook":1007,"twitter":1008},{"description":382,"title":1002},{"description":382,"title":1002},[1010],{"title":526,"slug":527},[1012],{"blocks":1013},[1014],{"type":437,"textBlock":1015},"\u003Cspan style=\"font-weight:400;\">Ad rotation refers to the practice of alternating different advertisements within a single placement to test performance and prevent ad fatigue. It allows advertisers to compare which ad versions drive better engagement and conversions.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Ad rotation settings include:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Optimized Rotation:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Platforms prioritize showing ads expected to perform best based on engagement data.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Even Rotation:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Ads are shown equally, useful for A/B testing.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Rotate Indefinitely:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Ads continue to show regardless of performance, suitable for long-term brand campaigns.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Ad rotation is available on platforms like Google Ads and Meta Ads Manager, allowing advertisers to test different headlines, images, and calls-to-action (CTAs).\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">When multiple ads are part of a campaign, the ad platform cycles through them to ensure each receives impressions. The platform collects performance data, such as click-through rates (CTR) and conversions, and then adjusts the rotation based on the selected setting. For instance, an online shoe retailer might rotate two different ad creatives—one featuring a discount and another highlighting free shipping—to determine which drives more purchases.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Prevents Ad Fatigue:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Reduces overexposure to the same ad.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Improves Campaign Performance:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Identifies which ads resonate most with the audience.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Supports A/B Testing:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Compares different ad elements to optimize creative strategies.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A skincare brand rotates ads with different taglines, such as “Clear Skin in 7 Days” and “Glow Naturally,” to measure which attracts more engagement. A fast-food chain tests video versus image ads to determine which format performs better in driving app orders.\u003C/span>\n\n ",{"uri":1017,"id":1018,"title":1019,"url":1020,"postDate":753,"dateUpdated":991,"slug":1021,"sectionHandle":373,"type":410,"authors":1022,"seo":1030,"categories":1038,"contentArea":1040,"siteName":371},"glossary/ad-scheduling","17617","Ad Scheduling","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-scheduling/","ad-scheduling",[1023],{"fullName":371,"asset":1024,"position":419,"bio":9,"linkedIn":9,"authorPage":1029},[1025],{"type":27,"image":1026,"mobileImage":1028},[1027],{"src":417,"alt":9},[],[],{"title":1031,"description":382,"advanced":1032,"keywords":1034,"social":1035},"Ad Scheduling | Pixis",{"canonical":9,"robots":1033},[],[],{"facebook":1036,"twitter":1037},{"description":382,"title":1031},{"description":382,"title":1031},[1039],{"title":526,"slug":527},[1041],{"blocks":1042},[1043],{"type":437,"textBlock":1044},"\u003Cspan style=\"font-weight:400;\">Ad scheduling, also known as dayparting, allows advertisers to choose specific times and days for their ads to run. This ensures ads reach audiences when they are most likely to engage or convert.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Popular scheduling options include:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Time-Based Scheduling:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Ads run during selected hours (e.g., 8 AM to 5 PM).\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Day-Based Scheduling:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Ads run on specific days (e.g., weekdays only).\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Custom Scheduling:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Combines day and time settings for maximum flexibility.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Platforms like Google Ads and Meta Ads Manager offer scheduling tools to optimize ad delivery based on business hours or peak shopping times.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Advertisers set their preferred schedule during campaign creation. Platforms then prioritize serving ads within those timeframes. Performance data such as conversion rates by hour helps refine future scheduling. For example, a local coffee shop may schedule Instagram ads between 6 AM and 10 AM to capture the morning crowd.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Increases Efficiency:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Limits ad spend to high-converting time windows.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Improves Relevance:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Reaches customers when they are most likely to purchase.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Supports Time-Sensitive Campaigns:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Ideal for flash sales or live events.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A pizza delivery service schedules ads during evenings and weekends when demand is highest. A fashion brand promotes limited-time offers on Instagram Stories only during peak shopping hours.\u003C/span>\n\n ",{"uri":1046,"id":1047,"title":1048,"url":1049,"postDate":753,"dateUpdated":1050,"slug":1051,"sectionHandle":373,"type":410,"authors":1052,"seo":1060,"categories":1068,"contentArea":1070,"siteName":371},"glossary/ad-server","17623","Ad Server","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-server/","2025-04-17T03:17:29-04:00","ad-server",[1053],{"fullName":371,"asset":1054,"position":419,"bio":9,"linkedIn":9,"authorPage":1059},[1055],{"type":27,"image":1056,"mobileImage":1058},[1057],{"src":417,"alt":9},[],[],{"title":1061,"description":382,"advanced":1062,"keywords":1064,"social":1065},"Ad Server | Pixis",{"canonical":9,"robots":1063},[],[],{"facebook":1066,"twitter":1067},{"description":382,"title":1061},{"description":382,"title":1061},[1069],{"title":526,"slug":527},[1071],{"blocks":1072},[1073],{"type":437,"textBlock":1074},"\u003Cspan style=\"font-weight:400;\">An ad server is a technology platform that manages, delivers, and tracks digital advertisements across websites, apps, and other digital spaces.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Ad servers perform key functions such as:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Ad Delivery:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Places ads on selected platforms based on targeting criteria.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Performance Tracking:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Measures impressions, clicks, and conversions.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Frequency Capping:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Limits how many times an ad is shown to the same user.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Popular ad servers include Google Ad Manager and Amazon Ad Server.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">When a user visits a website, the ad server selects the most relevant ad from a pool of advertisers. It then delivers the ad in milliseconds. The server collects performance data, such as click-through rates (CTR) and engagement metrics, which help advertisers optimize their campaigns. For example, a travel agency using an ad server may show ads for tropical destinations to users who recently searched for vacation deals.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Centralized Campaign Management:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Streamlines ad delivery across multiple platforms.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Real-Time Reporting:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Provides insights into ad performance.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Optimized Ad Targeting:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Matches ads to users based on behavior and preferences.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A fitness equipment brand uses an ad server to deliver banner ads across health and wellness blogs. A toy retailer manages both desktop and mobile ad placements through a single ad server for consistent performance tracking.\u003C/span>\n\n ",{"uri":1076,"id":1077,"title":1078,"url":1079,"postDate":753,"dateUpdated":1050,"slug":1080,"sectionHandle":373,"type":410,"authors":1081,"seo":1089,"categories":1097,"contentArea":1099,"siteName":371},"glossary/ad-stack","17629","Ad Stack","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-stack/","ad-stack",[1082],{"fullName":371,"asset":1083,"position":419,"bio":9,"linkedIn":9,"authorPage":1088},[1084],{"type":27,"image":1085,"mobileImage":1087},[1086],{"src":417,"alt":9},[],[],{"title":1090,"description":382,"advanced":1091,"keywords":1093,"social":1094},"Ad Stack | Pixis",{"canonical":9,"robots":1092},[],[],{"facebook":1095,"twitter":1096},{"description":382,"title":1090},{"description":382,"title":1090},[1098],{"title":526,"slug":527},[1100],{"blocks":1101},[1102],{"type":437,"textBlock":1103},"\u003Cspan style=\"font-weight:400;\">An ad stack is a collection of technologies and platforms that work together to manage, deliver, measure, and optimize digital advertisements. It includes components for buying, selling, serving, and tracking ads across multiple platforms and devices. Ad stacks streamline programmatic advertising, allowing advertisers and publishers to manage campaigns efficiently.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A typical ad stack consists of several essential components:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Demand-Side Platform (DSP):\u003C/b>\u003Cspan style=\"font-weight:400;\"> Allows advertisers to purchase ad inventory programmatically.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Supply-Side Platform (SSP):\u003C/b>\u003Cspan style=\"font-weight:400;\"> Helps publishers manage and sell ad inventory.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Ad Server:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Delivers ads to users and tracks impressions and clicks.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Data Management Platform (DMP):\u003C/b>\u003Cspan style=\"font-weight:400;\"> Collects and segments audience data for targeted advertising.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Analytics and Reporting Tools:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Provide insights on campaign performance and ROI.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Ad stacks can be integrated end-to-end through a single provider, such as Google Marketing Platform, or assembled from multiple third-party tools.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">The ad stack connects advertisers and publishers through programmatic advertising. When a user visits a website, the ad stack processes the user's data, triggers a real-time bidding (RTB) auction, and displays the winning ad. Each component communicates seamlessly to ensure ads are delivered to the right audience quickly and efficiently. For example, a sports apparel brand using an ad stack may simultaneously run video ads on YouTube, display ads on blogs, and search ads on Google—all managed from one central system.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Streamlines Campaign Management:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Consolidates tools for buying, serving, and analyzing ads.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Increases Efficiency:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Reduces manual effort through automation.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Enhances Targeting:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Uses audience data to deliver personalized ads.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Provides End-to-End Insights:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Tracks performance across multiple channels and platforms.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A luxury retailer uses a complete ad stack to run campaigns on social media, search engines, and display networks, tracking conversions in a unified dashboard. A streaming service employs an ad stack to manage ads across desktop, mobile, and connected TVs while using audience data for personalized recommendations.\u003C/span>\n\n ",{"uri":1105,"id":1106,"title":1107,"url":1108,"postDate":753,"dateUpdated":1109,"slug":1110,"sectionHandle":373,"type":410,"authors":1111,"seo":1119,"categories":1127,"contentArea":1129,"siteName":371},"glossary/ad-suppression","17635","Ad Suppression","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-suppression/","2025-04-17T03:17:30-04:00","ad-suppression",[1112],{"fullName":371,"asset":1113,"position":419,"bio":9,"linkedIn":9,"authorPage":1118},[1114],{"type":27,"image":1115,"mobileImage":1117},[1116],{"src":417,"alt":9},[],[],{"title":1120,"description":382,"advanced":1121,"keywords":1123,"social":1124},"Ad Suppression | Pixis",{"canonical":9,"robots":1122},[],[],{"facebook":1125,"twitter":1126},{"description":382,"title":1120},{"description":382,"title":1120},[1128],{"title":526,"slug":527},[1130],{"blocks":1131},[1132],{"type":437,"textBlock":1133},"\u003Cspan style=\"font-weight:400;\">Ad suppression is a digital advertising strategy that prevents specific users from seeing certain ads, ensuring that campaigns reach the most relevant audiences without wasting impressions. It is commonly used to exclude irrelevant audiences or avoid showing repetitive ads to users who have already converted.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Ad suppression is typically managed through suppression lists—databases of users who should not see a particular ad. Common suppression practices include:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Excluding Recent Buyers:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Prevents ads from being shown to customers who have just purchased.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Audience List Exclusions:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Removes users who are already subscribed or engaged.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Campaign-Level Suppression:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Avoids overlapping promotions within the same ad account.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Frequency-Based Suppression:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Stops ads from being shown too many times to the same user.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Platforms like Meta Ads Manager and Google Ads allow advertisers to upload suppression lists from their customer relationship management (CRM) systems to refine targeting.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Ad suppression works by comparing user profiles to suppression lists in real time. When a user from the list visits a platform, the ad server excludes them from seeing specific ads. For example, an online fashion retailer might suppress ads for a \"New Customer Discount\" campaign to users who recently made a purchase. Ad suppression is crucial in email retargeting campaigns, ensuring that customers who have already redeemed offers are not targeted with irrelevant promotions.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Reduces Wasted Ad Spend:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Prevents impressions on users unlikely to convert.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Improves Audience Relevance:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Focuses ad delivery on new or high-intent users.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Prevents Ad Fatigue:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Reduces overexposure to repetitive ads.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Increases Conversion Rates:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Ensures that ads reach users at the right stage of the buying journey.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A car dealership suppresses ads for a lease offer to customers who recently signed a contract, redirecting them to service and maintenance promotions. A subscription box service uses ad suppression to exclude current subscribers from acquisition campaigns, focusing on churned users instead.\u003C/span>\n\n ",{"uri":1135,"id":1136,"title":1137,"url":1138,"postDate":753,"dateUpdated":1109,"slug":1139,"sectionHandle":373,"type":410,"authors":1140,"seo":1148,"categories":1156,"contentArea":1158,"siteName":371},"glossary/ad-targeting","17641","Ad Targeting","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-targeting/","ad-targeting",[1141],{"fullName":371,"asset":1142,"position":419,"bio":9,"linkedIn":9,"authorPage":1147},[1143],{"type":27,"image":1144,"mobileImage":1146},[1145],{"src":417,"alt":9},[],[],{"title":1149,"description":382,"advanced":1150,"keywords":1152,"social":1153},"Ad Targeting | Pixis",{"canonical":9,"robots":1151},[],[],{"facebook":1154,"twitter":1155},{"description":382,"title":1149},{"description":382,"title":1149},[1157],{"title":526,"slug":527},[1159],{"blocks":1160},[1161],{"type":437,"textBlock":1162},"\u003Cspan style=\"font-weight:400;\">Ad targeting is the process of delivering digital ads to specific audiences based on criteria such as behavior, demographics, interests, and location. It ensures that ads reach users most likely to engage or convert, increasing the efficiency and effectiveness of advertising campaigns.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">There are several types of ad targeting strategies, including:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Demographic Targeting:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Focuses on characteristics such as age, gender, or income.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Behavioral Targeting:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Targets users based on past online actions, such as website visits or purchases.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Interest-Based Targeting:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Reaches users who engage with specific content categories.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Geotargeting:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Displays ads to users in a particular location.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Contextual Targeting:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Matches ads to the content of the webpage being viewed.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Retargeting:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Shows ads to users who previously interacted with a brand but didn’t convert.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Platforms like Meta Ads Manager, Google Ads, and TikTok Ads Manager offer extensive targeting options for advertisers.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Ad targeting uses data collected from cookies, social media activity, and search behavior to profile users. When a user visits a website, the ad platform compares their profile against the campaign’s targeting settings to decide which ad to serve. For example, a fitness brand may target users who have recently visited gym websites and purchased workout equipment. Machine learning algorithms continuously refine targeting by analyzing performance data and adjusting ad delivery to reach high-converting users.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Increases Ad Relevance:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Delivers ads to users most likely to be interested.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Boosts Conversion Rates:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Focuses on audiences with proven purchase intent.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Optimizes Ad Spend:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Reduces waste by excluding irrelevant audiences.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Supports Personalized Marketing:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Tailors messages based on user profiles and behaviors.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A cosmetics brand targets ads for anti-aging products to women over 40 who engage with skincare content on Instagram. A local pizza chain uses geotargeting to show ads only to users within a 5-mile radius of its locations. A travel agency uses behavioral targeting to reach users who recently searched for flights or hotels.\u003C/span>",{"uri":1164,"id":1165,"title":1166,"url":1167,"postDate":753,"dateUpdated":1168,"slug":1169,"sectionHandle":373,"type":410,"authors":1170,"seo":1178,"categories":1186,"contentArea":1188,"siteName":371},"glossary/ad-viewability","17647","Ad Viewability","https://pixis-brand-web-1dfin.sevalla.page/glossary/ad-viewability/","2025-04-17T03:17:31-04:00","ad-viewability",[1171],{"fullName":371,"asset":1172,"position":419,"bio":9,"linkedIn":9,"authorPage":1177},[1173],{"type":27,"image":1174,"mobileImage":1176},[1175],{"src":417,"alt":9},[],[],{"title":1179,"description":382,"advanced":1180,"keywords":1182,"social":1183},"Ad Viewability | Pixis",{"canonical":9,"robots":1181},[],[],{"facebook":1184,"twitter":1185},{"description":382,"title":1179},{"description":382,"title":1179},[1187],{"title":526,"slug":527},[1189],{"blocks":1190},[1191],{"type":437,"textBlock":1192},"\u003Cspan style=\"font-weight:400;\">Ad viewability measures whether an advertisement is actually seen by users, providing advertisers with insights into how effectively their ads are displayed. It ensures that advertisers pay only for ads that have the potential to engage their audience.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">The Media Rating Council (MRC) and the Interactive Advertising Bureau (IAB) define ad viewability standards as:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Display Ads:\u003C/b>\u003Cspan style=\"font-weight:400;\"> At least 50% of the ad must be visible for one continuous second.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Video Ads:\u003C/b>\u003Cspan style=\"font-weight:400;\"> At least 50% of the video player must be visible for at least two continuous seconds.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Rich Media Ads:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Interactive ads must be viewable for the time specified by the platform.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Platforms like Google Ads, DoubleVerify, and Moat provide ad viewability tracking and reporting.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Ad viewability is measured using tracking pixels or viewability tags that monitor when and how long an ad appears within a user’s screen. Viewability metrics are reported as a percentage, representing how many impressions were actually seen by users. For example, if a fashion retailer’s ad is served 1,000 times but only 600 impressions meet the visibility criteria, the viewability rate is 60%. Advertisers often use programmatic platforms to bid specifically on inventory with high viewability scores.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Reduces Wasted Spend:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Ensures advertisers pay only for visible impressions.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Improves Ad Effectiveness:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Measures actual exposure, not just delivery.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Optimizes Campaign Performance:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Identifies placements with high visibility rates.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Supports Better Ad Design:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Encourages placements in high-traffic and above-the-fold areas.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A luxury watch brand tracks ad viewability to ensure that its banner ads on premium lifestyle websites are fully seen. A mobile game developer adjusts placements to improve viewability rates by prioritizing rewarded video ads over interstitials. An electronics retailer uses viewability data to negotiate better placements with publishers.\u003C/span>",{"uri":1194,"id":1195,"title":1196,"url":1197,"postDate":753,"dateUpdated":1168,"slug":1198,"sectionHandle":373,"type":410,"authors":1199,"seo":1207,"categories":1215,"contentArea":1217,"siteName":371},"glossary/advantage","17653","Advantage+","https://pixis-brand-web-1dfin.sevalla.page/glossary/advantage/","advantage",[1200],{"fullName":371,"asset":1201,"position":419,"bio":9,"linkedIn":9,"authorPage":1206},[1202],{"type":27,"image":1203,"mobileImage":1205},[1204],{"src":417,"alt":9},[],[],{"title":1208,"description":382,"advanced":1209,"keywords":1211,"social":1212},"Advantage+ | Pixis",{"canonical":9,"robots":1210},[],[],{"facebook":1213,"twitter":1214},{"description":382,"title":1208},{"description":382,"title":1208},[1216],{"title":526,"slug":527},[1218],{"blocks":1219},[1220],{"type":437,"textBlock":1221},"\u003Cspan style=\"font-weight:400;\">Advantage+ is Meta’s automated ad solution that uses machine learning to streamline ad creation, placement, and audience targeting across platforms like Facebook and Instagram. It is designed to maximize campaign performance while reducing the need for manual adjustments.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Advantage+ offers several automation features:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Automated Placements:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Distributes ads across multiple formats and platforms, such as Reels, Stories, and Feeds.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Dynamic Creative Optimization:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Automatically tests and displays the best-performing combinations of images, headlines, and calls-to-action (CTAs).\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Audience Expansion:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Broadens targeting beyond selected audiences if it increases conversions.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Budget Optimization:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Allocates ad spend to the highest-performing placements in real-time.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">This solution is designed for businesses of all sizes, from local retailers to global e-commerce brands.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Advertisers provide assets such as images, videos, and headlines, set a budget, and define campaign objectives. Meta’s AI then creates multiple ad variations and tests them against different audiences. The algorithm continuously learns from engagement patterns and shifts ad delivery to the most effective combinations. For example, a fashion retailer running an Advantage+ campaign may see the platform automatically prioritize Reels over Stories if they generate higher engagement.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Simplifies Campaign Management:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Reduces the need for manual adjustments.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Maximizes Performance:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Uses AI to identify and scale the best-performing ad variations.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Saves Time:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Automates the testing and optimization process.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Boosts ROI:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Allocates budget to the highest-converting placements.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A home décor brand uses Advantage+ to promote seasonal collections, allowing Meta’s algorithm to optimize placements across Facebook and Instagram. A coffee shop runs Advantage+ campaigns to target local customers, with automated adjustments that prioritize ads with the best engagement.\u003C/span>",{"uri":1223,"id":1224,"title":1225,"url":1226,"postDate":753,"dateUpdated":1227,"slug":1228,"sectionHandle":373,"type":410,"authors":1229,"seo":1237,"categories":1245,"contentArea":1247,"siteName":371},"glossary/affiliate-advertising","17659","Affiliate Advertising","https://pixis-brand-web-1dfin.sevalla.page/glossary/affiliate-advertising/","2025-04-17T03:17:32-04:00","affiliate-advertising",[1230],{"fullName":371,"asset":1231,"position":419,"bio":9,"linkedIn":9,"authorPage":1236},[1232],{"type":27,"image":1233,"mobileImage":1235},[1234],{"src":417,"alt":9},[],[],{"title":1238,"description":382,"advanced":1239,"keywords":1241,"social":1242},"Affiliate Advertising | Pixis",{"canonical":9,"robots":1240},[],[],{"facebook":1243,"twitter":1244},{"description":382,"title":1238},{"description":382,"title":1238},[1246],{"title":526,"slug":527},[1248],{"blocks":1249},[1250],{"type":437,"textBlock":1251},"\u003Cspan style=\"font-weight:400;\">Affiliate advertising is a performance-based marketing model where businesses pay third-party partners, known as affiliates, for driving traffic or sales through referral links. It is a popular strategy for e-commerce brands to expand their reach without upfront advertising costs.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Affiliate advertising typically involves three key participants:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Advertiser (Merchant):\u003C/b>\u003Cspan style=\"font-weight:400;\"> The brand offering products or services.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Affiliate (Publisher):\u003C/b>\u003Cspan style=\"font-weight:400;\"> The promoter, which can be influencers, bloggers, or review sites.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Affiliate Network:\u003C/b>\u003Cspan style=\"font-weight:400;\"> The platform that tracks sales and manages payments.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Common payment structures include:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Pay-Per-Sale (PPS):\u003C/b>\u003Cspan style=\"font-weight:400;\"> The affiliate earns a commission for each sale.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Pay-Per-Lead (PPL):\u003C/b>\u003Cspan style=\"font-weight:400;\"> Payment is made for generating leads, such as email sign-ups.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Pay-Per-Click (PPC):\u003C/b>\u003Cspan style=\"font-weight:400;\"> Affiliates earn based on clicks, regardless of conversion.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">Affiliate platforms such as ShareASale, Amazon Associates, and Rakuten track conversions using unique referral links and cookies.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Advertisers create an affiliate program with commission structures and promotional materials. Affiliates promote the brand through their channels—such as blogs, social media, or YouTube—using unique tracking links. When a user clicks the link and completes a purchase, the affiliate earns a commission. For example, a beauty influencer promoting a skincare brand on Instagram may include an affiliate link in their bio, earning a percentage from every sale made through that link.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Cost-Effective Marketing:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Advertisers pay only for actual conversions.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Expands Reach:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Leverages affiliates’ audiences to promote products.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Boosts SEO:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Affiliate content often generates backlinks and increases search visibility.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Drives Conversions:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Affiliates with loyal followings drive high-intent traffic.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A fitness supplement brand partners with fitness influencers who promote their products using affiliate links on YouTube and TikTok. An online fashion retailer uses an affiliate network to recruit bloggers who create shopping guides with referral links. A travel booking site partners with influencers to promote vacation packages and pays commissions for each completed booking through their affiliate links.\u003C/span>",{"uri":1253,"id":1254,"title":1255,"url":1256,"postDate":753,"dateUpdated":1257,"slug":1258,"sectionHandle":373,"type":410,"authors":1259,"seo":1267,"categories":1275,"contentArea":1277,"siteName":371},"glossary/ai-a-b-testing","17431","AI A/B Testing","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-a-b-testing/","2025-04-17T03:17:13-04:00","ai-a-b-testing",[1260],{"fullName":371,"asset":1261,"position":419,"bio":9,"linkedIn":9,"authorPage":1266},[1262],{"type":27,"image":1263,"mobileImage":1265},[1264],{"src":417,"alt":9},[],[],{"title":1268,"description":382,"advanced":1269,"keywords":1271,"social":1272},"AI A/B Testing | Pixis",{"canonical":9,"robots":1270},[],[],{"facebook":1273,"twitter":1274},{"description":382,"title":1268},{"description":382,"title":1268},[1276],{"title":526,"slug":527},[1278],{"blocks":1279},[1280],{"type":437,"textBlock":1281},"\u003Cspan style=\"font-weight:400;\">AI A/B testing enhances the traditional process of split testing by using artificial intelligence to automate data collection, analysis, and optimization. This technology allows marketers to test and refine multiple elements simultaneously, such as headlines, images, and calls to action, without the need for extensive manual effort. AI can quickly identify high-performing variations, adjust them in real-time, and predict future outcomes based on past user behavior.\u003C/span>\n\u003Ch4>\u003Cb>What You Need to Know\u003C/b>\u003C/h4>\n\u003Cspan style=\"font-weight:400;\">AI A/B testing eliminates many limitations of manual testing by speeding up the process and improving precision. While traditional A/B testing often tests a single variation at a time, AI can handle multivariate tests, meaning several variables can be tested in parallel. For example, a marketing team might want to test different combinations of ad copy, visuals, and CTAs. AI-powered testing systems evaluate which combinations drive the best results for different audience segments and automatically adjust campaign parameters to optimize performance.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">AI continuously learns from campaign data, adapting to user behaviors and preferences over time. This makes it particularly effective for large-scale marketing initiatives where diverse audiences interact with content across multiple platforms.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI A/B testing involves a few core steps:\u003C/span>\n\u003Col>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Test Setup\u003C/b>\u003Cspan style=\"font-weight:400;\">: Marketers define the variables they want to test (e.g., ad text, images) and provide these variations to the AI system.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Traffic Distribution\u003C/b>\u003Cspan style=\"font-weight:400;\">: AI divides traffic across the variations, ensuring each test receives sufficient data.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Real-Time Analysis\u003C/b>\u003Cspan style=\"font-weight:400;\">: As users interact with the content, AI analyzes their behavior, measuring key performance metrics like conversions or engagement.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Optimization\u003C/b>\u003Cspan style=\"font-weight:400;\">: Based on real-time feedback, AI identifies patterns and trends, prioritizing the variations that perform best. Over time, the system can make data-driven adjustments to maximize campaign efficiency.\u003C/span>\u003C/li>\n\u003C/ol>\n\u003Cspan style=\"font-weight:400;\">AI’s ability to process data quickly and continuously allows marketers to refine their campaigns in near real-time, improving both short-term and long-term performance.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI A/B testing saves time by automating complex tasks and reducing the need for manual oversight. This enables marketing teams to focus on strategy and creativity rather than technical execution. The technology also enhances precision by identifying subtle patterns that human analysis might overlook. For example, AI can detect when certain visuals resonate more with specific demographics, allowing marketers to deliver more personalized experiences.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Additionally, AI testing minimizes the risk of error by ensuring statistically significant results. Faster optimization cycles mean that businesses can adapt to changes in user behavior quickly, keeping their campaigns competitive and relevant.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI A/B testing is widely used across industries and marketing channels. E-commerce companies optimize product pages by testing different layouts and images. Digital advertisers use AI to evaluate the effectiveness of ad creatives and targeting strategies. In email marketing, AI tests subject lines, body content, and send times to maximize open and click-through rates.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">AI-powered testing is also essential for personalized marketing campaigns. By analyzing customer data, AI can identify which variations are most effective for different audience segments and deliver tailored experiences that improve engagement and conversions.\u003C/span>",{"uri":1283,"id":1284,"title":1285,"url":1286,"postDate":1287,"dateUpdated":1288,"slug":1289,"sectionHandle":373,"type":410,"authors":1290,"seo":1298,"categories":1306,"contentArea":1310,"siteName":371},"glossary/ai-bandits","17677","AI Bandits","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-bandits/","2025-03-06T06:49:36-05:00","2025-04-17T03:17:33-04:00","ai-bandits",[1291],{"fullName":371,"asset":1292,"position":419,"bio":9,"linkedIn":9,"authorPage":1297},[1293],{"type":27,"image":1294,"mobileImage":1296},[1295],{"src":417,"alt":9},[],[],{"title":1299,"description":382,"advanced":1300,"keywords":1302,"social":1303},"AI Bandits | Pixis",{"canonical":9,"robots":1301},[],[],{"facebook":1304,"twitter":1305},{"description":382,"title":1299},{"description":382,"title":1299},[1307],{"title":1308,"slug":1309},"AI Fundamentals","ai-fundamentals",[1311],{"blocks":1312},[1313],{"type":437,"textBlock":1314},"AI bandits are algorithms that are used to make decisions in situations where there is uncertainty about the outcomes of different actions or where a choice needs to be made between a number of different options, but does not have enough information to make a fully informed decision. Based on information and experience gathered in previous input rounds, the algorithms are expected to make decisions in favor of maximizing a certain reward or objective. AI bandits allow AI systems to learn and adapt to changing situations in real time, making them more effective at achieving their objectives.",{"uri":1316,"id":1317,"title":1318,"url":1319,"postDate":753,"dateUpdated":1257,"slug":1320,"sectionHandle":373,"type":410,"authors":1321,"seo":1329,"categories":1337,"contentArea":1339,"siteName":371},"glossary/ai-content-generation","17437","AI Content Generation","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-content-generation/","ai-content-generation",[1322],{"fullName":371,"asset":1323,"position":419,"bio":9,"linkedIn":9,"authorPage":1328},[1324],{"type":27,"image":1325,"mobileImage":1327},[1326],{"src":417,"alt":9},[],[],{"title":1330,"description":382,"advanced":1331,"keywords":1333,"social":1334},"AI Content Generation | Pixis",{"canonical":9,"robots":1332},[],[],{"facebook":1335,"twitter":1336},{"description":382,"title":1330},{"description":382,"title":1330},[1338],{"title":526,"slug":527},[1340],{"blocks":1341},[1342],{"type":437,"textBlock":1343},"\u003Cspan style=\"font-weight:400;\">AI content generation refers to the process of creating various types of content—such as written articles, ad copy, product descriptions, and videos—using artificial intelligence. These tools leverage natural language processing (NLP) and machine learning algorithms to produce content that aligns with specific prompts or business needs.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI content generation has become an essential tool for businesses that require content at scale. Traditional content creation can be time-consuming and resource-intensive, especially when it involves personalized messaging for multiple customer segments. AI automates much of this process by generating high-quality, human-like content quickly and efficiently. This includes everything from generating blog post outlines to writing hundreds of unique product descriptions for an online store.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Advanced AI models, such as large language models, are trained on vast amounts of text data, enabling them to understand context, tone, and style. However, while AI can streamline content production, human oversight is still necessary to ensure the content is accurate, creative, and aligned with brand guidelines.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI content tools typically start with user inputs, such as a topic prompt or specific keywords. The AI model then analyzes patterns in its training data to generate content that fits the input criteria. For example, if a marketer asks the AI to write an article about \"AI in advertising,\" the tool will create a draft by assembling relevant information, complete with headings and key points.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">More advanced AI platforms can also analyze content performance data to suggest improvements. They might recommend optimizing content length, keyword placement, or tone to better engage the target audience.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI content generation offers significant time savings by automating repetitive tasks. Marketers can quickly produce multiple variations of ad copy or landing page content, allowing for faster campaign launches. AI also allows businesses to tailor content to different audience segments at scale.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Consistency is another key advantage. AI ensures that content adheres to brand voice and style guidelines, even when producing large volumes of material.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI content generation is widely used in e-commerce, where businesses need to create product descriptions, promotional emails, and dynamic ad content. Media organizations use AI to generate news summaries and SEO-optimized articles. In digital advertising, AI produces personalized ad headlines and body text designed to resonate with specific audience segments.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">AI content tools are also valuable for social media marketing, where they help brands maintain a consistent posting schedule by automating content creation and optimization.\u003C/span>",{"uri":1345,"id":1346,"title":1347,"url":1348,"postDate":753,"dateUpdated":1349,"slug":1350,"sectionHandle":373,"type":410,"authors":1351,"seo":1359,"categories":1367,"contentArea":1369,"siteName":371},"glossary/ai-creative-design","17443","AI Creative Design","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-creative-design/","2025-04-17T03:17:14-04:00","ai-creative-design",[1352],{"fullName":371,"asset":1353,"position":419,"bio":9,"linkedIn":9,"authorPage":1358},[1354],{"type":27,"image":1355,"mobileImage":1357},[1356],{"src":417,"alt":9},[],[],{"title":1360,"description":382,"advanced":1361,"keywords":1363,"social":1364},"AI Creative Design | Pixis",{"canonical":9,"robots":1362},[],[],{"facebook":1365,"twitter":1366},{"description":382,"title":1360},{"description":382,"title":1360},[1368],{"title":526,"slug":527},[1370],{"blocks":1371},[1372],{"type":437,"textBlock":1373},"\u003Cspan style=\"font-weight:400;\">AI creative design involves using artificial intelligence to generate, modify, or enhance visual content. These tools assist in creating marketing assets such as social media posts, banners, and advertisements by automating tasks like layout adjustments, image editing, and template generation.\u003C/span>\n\u003Ch4>\u003Cb>What You Need to Know\u003C/b>\u003C/h4>\n\u003Cspan style=\"font-weight:400;\">Traditionally, design work requires manual effort to create and modify visuals. AI-powered creative tools speed up this process by providing automated design suggestions based on best practices and engagement data. These tools can analyze audience preferences, recommending the most effective color schemes, typography, and image placements for a campaign.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">AI creative design supports both designers and non-designers, and enables faster content production without sacrificing quality. It is especially useful for businesses that need to produce a high volume of visuals across different platforms and formats.\u003C/span>\n\u003Ch4>\u003Cb>How It Works\u003C/b>\u003C/h4>\n\u003Cspan style=\"font-weight:400;\">AI design tools analyze performance data from previous campaigns to learn which design elements perform well with specific audiences. For example, an AI system might identify that certain colors or image styles generate higher engagement on social media. Marketers can then use this information to create optimized visuals.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">These tools also automate repetitive tasks, such as resizing images for different platforms or generating multiple design variations for A/B testing.\u003C/span>\n\u003Ch4>\u003Cb>Advantages\u003C/b>\u003C/h4>\n\u003Cspan style=\"font-weight:400;\">AI creative design tools improve efficiency by speeding up the production process. They help maintain brand consistency by applying predefined design rules automatically. AI also enhances personalization and allows marketers to tailor visuals for different audience segments without the need for extensive manual work.\u003C/span>\n\u003Ch4>\u003Cb>Applications and Use Cases\u003C/b>\u003C/h4>\n\u003Cspan style=\"font-weight:400;\">AI creative tools are commonly used in social media marketing, where rapid content production is needed. E-commerce companies rely on AI to create promotional banners and product images optimized for various ad platforms. Marketing teams use these tools to generate visuals for email campaigns, landing pages, and display ads.\u003C/span>",{"uri":1375,"id":1376,"title":1377,"url":1378,"postDate":753,"dateUpdated":1349,"slug":1379,"sectionHandle":373,"type":410,"authors":1380,"seo":1388,"categories":1396,"contentArea":1398,"siteName":371},"glossary/ai-customer-segmentation","17449","AI Customer Segmentation","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-customer-segmentation/","ai-customer-segmentation",[1381],{"fullName":371,"asset":1382,"position":419,"bio":9,"linkedIn":9,"authorPage":1387},[1383],{"type":27,"image":1384,"mobileImage":1386},[1385],{"src":417,"alt":9},[],[],{"title":1389,"description":382,"advanced":1390,"keywords":1392,"social":1393},"AI Customer Segmentation | Pixis",{"canonical":9,"robots":1391},[],[],{"facebook":1394,"twitter":1395},{"description":382,"title":1389},{"description":382,"title":1389},[1397],{"title":526,"slug":527},[1399],{"blocks":1400},[1401],{"type":437,"textBlock":1402},"\u003Cspan style=\"font-weight:400;\">AI customer segmentation uses machine learning to divide a business’s customer base into distinct groups based on data such as behavior, demographics, or preferences. This enables companies to deliver more relevant and personalized marketing experiences to each segment, ultimately improving engagement, conversion rates, and customer satisfaction.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Traditional segmentation involves creating customer groups using manual criteria, such as age, gender, location, or past purchases. AI enhances this process by analyzing vast amounts of data to identify patterns that are difficult for humans to detect. AI can find subtle correlations between variables, such as the relationship between purchase frequency and product preferences for a more refined and dynamic segmentation.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Unlike static segmentation, which may rely on historical data alone, AI-driven segmentation continuously updates as new data becomes available. This real-time adaptability ensures that businesses stay aligned with their customers’ evolving needs and preferences.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, an online retailer might use AI to identify a segment of customers who prefer eco-friendly products. The system analyzes data such as product page views, search queries, and purchase history to define this segment. Marketing teams can then craft targeted messages that promote sustainability-focused products to this group.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI models analyze customer data from multiple sources, such as transaction records, website interactions, and customer feedback. These models cluster customers with similar characteristics and behaviors into distinct groups. Businesses can view detailed profiles of these segments and create marketing strategies that match each group’s needs.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Over time, AI refines the segmentation based on how customers interact with marketing efforts. For example, if a particular promotion performs better with one segment than another, the AI system might adjust the segment definitions to reflect this new insight.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI customer segmentation improves targeting precision, which leads to higher engagement and conversion rates. Marketers can develop campaigns tailored to each group, increasing the likelihood that customers will respond positively. This approach also reduces inefficiencies, as businesses can avoid wasting resources on broad, untargeted marketing efforts.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">AI provides deeper insights than traditional methods by analyzing complex relationships in customer data. For example, it can reveal behavioral triggers, such as when customers are most likely to buy based on their browsing patterns or social media activity.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Retailers use AI segmentation to offer personalized product recommendations and develop unique engagement strategies by identifying key user segments and their needs.\u003C/span>",{"uri":1404,"id":1405,"title":1406,"url":1407,"postDate":1408,"dateUpdated":1409,"slug":1410,"sectionHandle":373,"type":410,"authors":1411,"seo":1419,"categories":1427,"contentArea":1429,"siteName":371},"glossary/ai-group","17695","AI Group","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-group/","2025-03-06T06:53:44-05:00","2025-04-17T03:17:34-04:00","ai-group",[1412],{"fullName":371,"asset":1413,"position":419,"bio":9,"linkedIn":9,"authorPage":1418},[1414],{"type":27,"image":1415,"mobileImage":1417},[1416],{"src":417,"alt":9},[],[],{"title":1420,"description":382,"advanced":1421,"keywords":1423,"social":1424},"AI Group | Pixis",{"canonical":9,"robots":1422},[],[],{"facebook":1425,"twitter":1426},{"description":382,"title":1420},{"description":382,"title":1420},[1428],{"title":526,"slug":527},[1430],{"blocks":1431},[1432],{"type":437,"textBlock":1433},"An AI Group, on Pixis AI Optimizer, is a list of ad sets or campaigns that have similar objectives, budget settings, bid strategy, and attribution settings which are optimized for performance by customizing bid and budget.",{"uri":1435,"id":1436,"title":1437,"url":1438,"postDate":1439,"dateUpdated":1288,"slug":1440,"sectionHandle":373,"type":410,"authors":1441,"seo":1449,"categories":1457,"contentArea":1459,"siteName":371},"glossary/ai-infrastructure","17671","AI Infrastructure","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-infrastructure/","2025-03-06T06:06:01-05:00","ai-infrastructure",[1442],{"fullName":371,"asset":1443,"position":419,"bio":9,"linkedIn":9,"authorPage":1448},[1444],{"type":27,"image":1445,"mobileImage":1447},[1446],{"src":417,"alt":9},[],[],{"title":1450,"description":382,"advanced":1451,"keywords":1453,"social":1454},"AI Infrastructure | Pixis",{"canonical":9,"robots":1452},[],[],{"facebook":1455,"twitter":1456},{"description":382,"title":1450},{"description":382,"title":1450},[1458],{"title":1308,"slug":1309},[1460],{"blocks":1461},[1462],{"type":437,"textBlock":1463},"Pixis’ codeless AI Infrastructure refers to the underlying system of pre-trained, customizable AI models and deep-learning technologies that enable training, testing, experimentation and deployment of Artificial Intelligence-powered marketing strategies.\n\nPixis’ codeless AI infrastructure consists of 120+ (and growing) AI models trained to optimize marketing and demand generation.",{"uri":1465,"id":1466,"title":1467,"url":1468,"postDate":1469,"dateUpdated":1470,"slug":1471,"sectionHandle":373,"type":410,"authors":1472,"seo":1480,"categories":1488,"contentArea":1490,"siteName":371},"glossary/ai-model","17701","AI Model","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-model/","2025-03-06T06:57:16-05:00","2025-04-17T03:17:35-04:00","ai-model",[1473],{"fullName":371,"asset":1474,"position":419,"bio":9,"linkedIn":9,"authorPage":1479},[1475],{"type":27,"image":1476,"mobileImage":1478},[1477],{"src":417,"alt":9},[],[],{"title":1481,"description":382,"advanced":1482,"keywords":1484,"social":1485},"AI Model | Pixis",{"canonical":9,"robots":1483},[],[],{"facebook":1486,"twitter":1487},{"description":382,"title":1481},{"description":382,"title":1481},[1489],{"title":1308,"slug":1309},[1491],{"blocks":1492},[1493],{"type":437,"textBlock":1494},"An AI Model is a set of algorithms that allow a machine to perform tasks that mimic human intelligence. These tasks could include; understanding language, recognizing patterns, or making decisions based on data. In this way, an AI model allows a machine to perform tasks that would otherwise require human intelligence, allowing it to make decisions and predictions based on data in a way that is similar to how a human would. Common AI models are expert systems, natural language processing, speech recognition, and machine vision. At Pixis, AI models analyze historical data points and recommend changes to provide improved cost and efficiency.",{"uri":1496,"id":1497,"title":1498,"url":1499,"postDate":1500,"dateUpdated":1470,"slug":1501,"sectionHandle":373,"type":410,"authors":1502,"seo":1510,"categories":1518,"contentArea":1520,"siteName":371},"glossary/ai-optimizer","17707","AI Optimizer","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-optimizer/","2025-03-06T06:58:26-05:00","ai-optimizer",[1503],{"fullName":371,"asset":1504,"position":419,"bio":9,"linkedIn":9,"authorPage":1509},[1505],{"type":27,"image":1506,"mobileImage":1508},[1507],{"src":417,"alt":9},[],[],{"title":1511,"description":382,"advanced":1512,"keywords":1514,"social":1515},"AI Optimizer | Pixis",{"canonical":9,"robots":1513},[],[],{"facebook":1516,"twitter":1517},{"description":382,"title":1511},{"description":382,"title":1511},[1519],{"title":1308,"slug":1309},[1521],{"blocks":1522},[1523],{"type":437,"textBlock":1524},"Pixis AI Optimizer is a Google Chrome extension that allows users to quickly and easily access Pixis' three codeless AI engines on over 40 platforms without any additional installations. The extension unlocks a self-evolving neural network that includes dozens of proprietary AI models for marketing optimization in just 8 seconds.",{"uri":1526,"id":1527,"title":1528,"url":1529,"postDate":753,"dateUpdated":1530,"slug":1531,"sectionHandle":373,"type":410,"authors":1532,"seo":1540,"categories":1548,"contentArea":1550,"siteName":371},"glossary/ai-training","17455","AI Training","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-training/","2025-04-17T03:17:15-04:00","ai-training",[1533],{"fullName":371,"asset":1534,"position":419,"bio":9,"linkedIn":9,"authorPage":1539},[1535],{"type":27,"image":1536,"mobileImage":1538},[1537],{"src":417,"alt":9},[],[],{"title":1541,"description":382,"advanced":1542,"keywords":1544,"social":1545},"AI Training | Pixis",{"canonical":9,"robots":1543},[],[],{"facebook":1546,"twitter":1547},{"description":382,"title":1541},{"description":382,"title":1541},[1549],{"title":526,"slug":527},[1551],{"blocks":1552},[1553],{"type":437,"textBlock":1554},"\u003Cspan style=\"font-weight:400;\">AI training refers to the process of teaching machine learning models to perform tasks by feeding them large amounts of relevant data. The model analyzes this data to recognize patterns and make predictions. Training is critical to the success of AI systems, as it determines how accurately they can perform their intended functions.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI models do not inherently know how to solve problems. They require structured training to learn from examples. For example, a model designed to predict customer churn needs data on past customer behavior, including which customers left and which stayed. The model uses this data to identify trends and generate predictions about future customer retention.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Training often occurs in phases. Initially, the model trains on a dataset where the correct outcomes are known. This is called supervised learning. The model’s performance improves through repeated exposure to the data and continuous fine-tuning of its internal algorithms. Once trained, the model can analyze new data and make accurate predictions.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">The AI training process involves several key steps:\u003C/span>\n\u003Col>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Data Collection\u003C/b>\u003Cspan style=\"font-weight:400;\">: The model needs a comprehensive dataset that includes relevant features for the task.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Data Labeling\u003C/b>\u003Cspan style=\"font-weight:400;\">: In supervised learning, each data point must have an associated label (e.g., whether a customer churned or not).\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Model Training\u003C/b>\u003Cspan style=\"font-weight:400;\">: The model analyzes the labeled data and adjusts its parameters to reduce errors.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Evaluation\u003C/b>\u003Cspan style=\"font-weight:400;\">: After training, the model is tested on a separate dataset to measure its accuracy.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Iteration\u003C/b>\u003Cspan style=\"font-weight:400;\">: If the performance is unsatisfactory, the training process is repeated with refined data or adjusted parameters.\u003C/span>\u003C/li>\n\u003C/ol>\n\u003Cspan style=\"font-weight:400;\">Models often require regular retraining to remain effective in dynamic environments where customer behavior or market conditions change frequently.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Proper AI training leads to models that provide reliable, actionable insights. Businesses can automate complex processes, such as demand forecasting or fraud detection, based on the predictions generated by well-trained models. Training also enhances scalability. Once an AI system is trained, it can handle large volumes of data without human intervention.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">However, the quality of training data is critical. Poor or biased data can lead to inaccurate predictions, which can undermine business decisions. Therefore, businesses must invest in high-quality data collection and regular model evaluation.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Retailers train AI models to predict inventory needs and optimize supply chains. Marketing teams use AI models trained on customer data to create personalized experiences.\u003C/span>",{"uri":1556,"id":1557,"title":1558,"url":1559,"postDate":753,"dateUpdated":1530,"slug":1560,"sectionHandle":373,"type":410,"authors":1561,"seo":1569,"categories":1577,"contentArea":1579,"siteName":371},"glossary/ai-video-content","17461","AI Video Content","https://pixis-brand-web-1dfin.sevalla.page/glossary/ai-video-content/","ai-video-content",[1562],{"fullName":371,"asset":1563,"position":419,"bio":9,"linkedIn":9,"authorPage":1568},[1564],{"type":27,"image":1565,"mobileImage":1567},[1566],{"src":417,"alt":9},[],[],{"title":1570,"description":382,"advanced":1571,"keywords":1573,"social":1574},"AI Video Content | Pixis",{"canonical":9,"robots":1572},[],[],{"facebook":1575,"twitter":1576},{"description":382,"title":1570},{"description":382,"title":1570},[1578],{"title":526,"slug":527},[1580],{"blocks":1581},[1582],{"type":437,"textBlock":1583},"\u003Cspan style=\"font-weight:400;\">AI video content refers to the creation and optimization of video assets using artificial intelligence. AI tools assist with script generation, scene selection, editing, and even creating synthetic characters or voiceovers. These tools help businesses produce high-quality videos quickly and at scale.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Video content is increasingly important for digital marketing. However, producing engaging videos can be resource-intensive. AI simplifies this process by automating various stages of production. For example, AI can generate scripts based on data about audience preferences. It can also suggest optimal video lengths, transitions, and visuals to maximize engagement.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Advanced AI platforms can analyze performance data from previous videos and recommend changes to improve results. This allows marketers to continuously refine their video strategies without extensive manual effort.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI video tools typically begin with user inputs, such as a video topic or target audience. The AI system generates a storyboard and suggests visuals, audio tracks, and voiceovers. It can also automate tasks like video cropping and resizing to fit different social media platforms.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Once the video is published, AI tracks metrics like views, watch time, and click-through rates. It analyzes these metrics to provide recommendations for future videos.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AI video tools reduce production time by automating repetitive tasks. Businesses can create personalized video content for different audience segments without significant additional effort. AI also enhances performance optimization by providing data-driven recommendations for improving engagement.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">These tools are particularly useful for scaling video marketing campaigns. Instead of relying on costly, time-consuming manual editing, companies can quickly produce and iterate on videos across multiple channels.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">E-commerce businesses use AI-generated videos to showcase products with dynamic visuals and personalized messaging. Social media marketers create video ads optimized for different platforms. \u003C/span>",{"uri":1585,"id":1586,"title":1587,"url":1588,"postDate":1589,"dateUpdated":1288,"slug":1590,"sectionHandle":373,"type":410,"authors":1591,"seo":1599,"categories":1607,"contentArea":1609,"siteName":371},"glossary/artificial-neural-networks","17683","Artificial Neural Networks","https://pixis-brand-web-1dfin.sevalla.page/glossary/artificial-neural-networks/","2025-03-06T06:51:53-05:00","artificial-neural-networks",[1592],{"fullName":371,"asset":1593,"position":419,"bio":9,"linkedIn":9,"authorPage":1598},[1594],{"type":27,"image":1595,"mobileImage":1597},[1596],{"src":417,"alt":9},[],[],{"title":1600,"description":382,"advanced":1601,"keywords":1603,"social":1604},"Artificial Neural Networks | Pixis",{"canonical":9,"robots":1602},[],[],{"facebook":1605,"twitter":1606},{"description":382,"title":1600},{"description":382,"title":1600},[1608],{"title":1308,"slug":1309},[1610],{"blocks":1611},[1612],{"type":437,"textBlock":1613},"Artificial Neural Networks (or Neural Networks) are modeled on the way neural networks of the biological brain function. They consist of a series of interconnected nodes, or \"neurons,\" which are essentially small processing units that can analyze and interpret data. These networks are trained to recognize patterns and make decisions based on that data, allowing them to perform tasks such as recognizing faces, translating languages, or even playing games.\n\nNeural networks function by using input data to adjust the connections between the neurons to recognize patterns and make accurate predictions. For example, if you want a machine to recognize and identify cats in an image, its neural network must be fed, or trained on, a large number of cat images. Once a neural network has been trained, it can be used to make predictions or decisions based on new input data. Neural networks are used in a wide range of applications, including image recognition, Natural Language Processing (NLP), and even self-driving cars.",{"uri":1615,"id":1616,"title":1617,"url":1618,"postDate":1619,"dateUpdated":375,"slug":1620,"sectionHandle":373,"type":410,"authors":1621,"seo":1629,"categories":1637,"contentArea":1639,"siteName":371},"glossary/attention","17725","Attention","https://pixis-brand-web-1dfin.sevalla.page/glossary/attention/","2025-03-06T07:00:44-05:00","attention",[1622],{"fullName":371,"asset":1623,"position":419,"bio":9,"linkedIn":9,"authorPage":1628},[1624],{"type":27,"image":1625,"mobileImage":1627},[1626],{"src":417,"alt":9},[],[],{"title":1630,"description":382,"advanced":1631,"keywords":1633,"social":1634},"Attention | Pixis",{"canonical":9,"robots":1632},[],[],{"facebook":1635,"twitter":1636},{"description":382,"title":1630},{"description":382,"title":1630},[1638],{"title":1308,"slug":1309},[1640],{"blocks":1641},[1642],{"type":437,"textBlock":1643},"Attention refers to the ability of a model to focus on a specific subset of its inputs, or \"attend\" to them, while processing a given task. It enables machines to focus on the most relevant information and ignore irrelevant or less important input. For example, in Natural Language Processing (NLP), an attention mechanism might allow a language model to focus on certain words or phrases in a sentence to better understand the meaning or intent of the text. Attention mechanisms have become an important tool in deep learning, as they help models handle large and complex input data and perform tasks that require selective focus, or \"attention\" to certain elements of the input.",{"uri":1645,"id":1646,"title":1647,"url":1648,"postDate":753,"dateUpdated":1227,"slug":1649,"sectionHandle":373,"type":410,"authors":1650,"seo":1658,"categories":1666,"contentArea":1668,"siteName":371},"glossary/attribution-modeling","17665","Attribution Modeling","https://pixis-brand-web-1dfin.sevalla.page/glossary/attribution-modeling/","attribution-modeling",[1651],{"fullName":371,"asset":1652,"position":419,"bio":9,"linkedIn":9,"authorPage":1657},[1653],{"type":27,"image":1654,"mobileImage":1656},[1655],{"src":417,"alt":9},[],[],{"title":1659,"description":382,"advanced":1660,"keywords":1662,"social":1663},"Attribution Modeling | Pixis",{"canonical":9,"robots":1661},[],[],{"facebook":1664,"twitter":1665},{"description":382,"title":1659},{"description":382,"title":1659},[1667],{"title":526,"slug":527},[1669],{"blocks":1670},[1671],{"type":437,"textBlock":1672},"\u003Cspan style=\"font-weight:400;\">Attribution modeling is a framework used to analyze and assign credit to different marketing touchpoints in a customer's journey. It helps businesses understand which ads, platforms, or campaigns contribute most to conversions, such as purchases or sign-ups.\u003C/span>\n\n\u003Cb>What You Should Know\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Attribution modeling is crucial for optimizing ad spend and improving marketing performance. It determines how credit for a conversion is distributed across multiple touchpoints. Common attribution models include:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>First-Touch Attribution:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Assigns 100% credit to the first interaction.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Last-Touch Attribution:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Credits the final touchpoint before conversion.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Linear Attribution:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Distributes credit equally across all touchpoints.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Time-Decay Attribution:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Gives more credit to interactions closer to the conversion.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Position-Based Attribution:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Assigns 40% credit to the first and last touchpoints and splits the remaining 20% across others.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Data-Driven Attribution:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Uses machine learning to assign credit based on actual user behavior patterns.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>How It Works\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">Attribution modeling collects data from customer interactions, such as clicks, video views, and social media engagements. Platforms like Google Analytics and Meta Ads Manager use tracking pixels and UTM parameters to map the customer journey. The chosen model then distributes conversion credit across the touchpoints. For example, if a customer first discovers a shoe brand through a Facebook ad, reads a blog review, and finally clicks a Google search ad to purchase, the attribution model determines how much credit each touchpoint receives.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Optimizes Marketing Budget:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Identifies high-performing channels for better ad spend allocation.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Improves Campaign Strategy:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Highlights which platforms drive conversions at different stages of the funnel.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Enhances Customer Journey Insights:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Provides a clearer understanding of how users interact with ads before purchasing.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Supports Multi-Channel Campaigns:\u003C/b>\u003Cspan style=\"font-weight:400;\"> Measures the combined impact of social, search, email, and display ads.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cb>Applications and Use Cases\u003C/b>\u003Cb>\n\u003C/b>\u003Cspan style=\"font-weight:400;\">A beauty brand uses time-decay attribution to identify that Instagram Stories drive early engagement, but email campaigns close the sale. A travel agency employs data-driven attribution to discover that customers who watch their YouTube travel guides are more likely to book trips after seeing retargeting ads. A fashion retailer combines Google Ads and social media insights to optimize their holiday campaign, focusing more on the channels driving final conversions.\u003C/span>\n\n ",{"uri":1674,"id":1675,"title":1676,"url":1677,"postDate":753,"dateUpdated":1678,"slug":1679,"sectionHandle":373,"type":410,"authors":1680,"seo":1688,"categories":1696,"contentArea":1698,"siteName":371},"glossary/automated-ad-campaigns","17467","Automated Ad Campaigns","https://pixis-brand-web-1dfin.sevalla.page/glossary/automated-ad-campaigns/","2025-04-17T03:17:16-04:00","automated-ad-campaigns",[1681],{"fullName":371,"asset":1682,"position":419,"bio":9,"linkedIn":9,"authorPage":1687},[1683],{"type":27,"image":1684,"mobileImage":1686},[1685],{"src":417,"alt":9},[],[],{"title":1689,"description":382,"advanced":1690,"keywords":1692,"social":1693},"Automated Ad Campaigns | Pixis",{"canonical":9,"robots":1691},[],[],{"facebook":1694,"twitter":1695},{"description":382,"title":1689},{"description":382,"title":1689},[1697],{"title":526,"slug":527},[1699],{"blocks":1700},[1701],{"type":437,"textBlock":1702},"\u003Cspan style=\"font-weight:400;\">Automated ad campaigns rely on technology to manage key aspects of digital advertising, such as bidding, targeting, and content optimization. AI and machine learning algorithms analyze data in real-time to maximize ad performance with minimal manual intervention.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Traditional ad management requires marketers to manually adjust campaign settings, such as bid strategies and audience targeting. Automated ad platforms streamline this process by using AI to make these adjustments dynamically. The system analyzes data, including user behavior and conversion rates, to optimize ad placements and budgets in real time.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Automation allows businesses to run large, complex campaigns across multiple platforms while maintaining high efficiency. Marketers can focus on strategic goals, knowing that the system continuously works to improve performance.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Automated ad platforms use machine learning models to analyze campaign data. Based on performance insights, the system adjusts bidding strategies, reallocates budgets, and refines targeting parameters. For example, if an ad performs well with a specific demographic, the platform may prioritize serving ads to that group.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Marketers set goals for the campaign, such as maximizing conversions or reducing cost per click (CPC). The platform uses these goals to guide optimization decisions.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Automation improves efficiency by reducing the need for manual adjustments. Businesses can achieve better results through real-time optimization, often leading to higher returns on ad spend (ROAS). Automated systems also provide scalability, allowing marketers to manage campaigns across multiple channels without overburdening their teams.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Additionally, automated platforms provide detailed performance insights, helping businesses refine their advertising strategies over time.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Automated ad campaigns are common in industries with high digital marketing investments, such as e-commerce, technology, and entertainment. Platforms like Google Ads and Meta’s ad manager use automation to optimize search and social media campaigns. But third-party AI platforms like Pixis can also help businesses increase conversions and reduce advertising costs by leveraging AI-driven decision-making.\u003C/span>",{"uri":1704,"id":1705,"title":1706,"url":1707,"postDate":1708,"dateUpdated":1409,"slug":1709,"sectionHandle":373,"type":410,"authors":1710,"seo":1718,"categories":1726,"contentArea":1728,"siteName":371},"glossary/autoregressive-language-model","17689","Autoregressive Language Model","https://pixis-brand-web-1dfin.sevalla.page/glossary/autoregressive-language-model/","2025-03-06T06:52:53-05:00","autoregressive-language-model",[1711],{"fullName":371,"asset":1712,"position":419,"bio":9,"linkedIn":9,"authorPage":1717},[1713],{"type":27,"image":1714,"mobileImage":1716},[1715],{"src":417,"alt":9},[],[],{"title":1719,"description":382,"advanced":1720,"keywords":1722,"social":1723},"Autoregressive Language Model | Pixis",{"canonical":9,"robots":1721},[],[],{"facebook":1724,"twitter":1725},{"description":382,"title":1719},{"description":382,"title":1719},[1727],{"title":1308,"slug":1309},[1729],{"blocks":1730},[1731],{"type":437,"textBlock":1732},"An autoregressive language model is a type of Artificial Intelligence (AI) model that is used to predict the next word in a sentence, or sequence of words, by using patterns and trends in language. It does so by contextually analyzing the preceding words in a sentence to predict what the next word might be. This type of model is used in Natural Language Processing (NLP) tasks, such as language translation or text generation.",{"uri":1734,"id":1735,"title":1736,"url":1737,"postDate":1738,"dateUpdated":506,"slug":1739,"sectionHandle":373,"type":410,"authors":1740,"seo":1748,"categories":1756,"contentArea":1758,"siteName":371},"glossary/autoregressive-models","17719","Autoregressive Models","https://pixis-brand-web-1dfin.sevalla.page/glossary/autoregressive-models/","2025-03-06T07:00:05-05:00","autoregressive-models",[1741],{"fullName":371,"asset":1742,"position":419,"bio":9,"linkedIn":9,"authorPage":1747},[1743],{"type":27,"image":1744,"mobileImage":1746},[1745],{"src":417,"alt":9},[],[],{"title":1749,"description":382,"advanced":1750,"keywords":1752,"social":1753},"Autoregressive Models | Pixis",{"canonical":9,"robots":1751},[],[],{"facebook":1754,"twitter":1755},{"description":382,"title":1749},{"description":382,"title":1749},[1757],{"title":1308,"slug":1309},[1759],{"blocks":1760},[1761],{"type":437,"textBlock":1762},"Autoregressive Models are a class of statistical models that analyze and predict time series data - basically a machine’s way of measuring and analyzing the correlation between different observations at different time instances. These models are used to forecast and make accurate predictions based on past trends. They are also used to identify patterns and trends, and for predictive modeling based on the underlying dynamics of data.",{"uri":1764,"id":1765,"title":1766,"url":1767,"postDate":753,"dateUpdated":1678,"slug":1768,"sectionHandle":373,"type":410,"authors":1769,"seo":1777,"categories":1785,"contentArea":1787,"siteName":371},"glossary/average-order-value-aov","17473","Average Order Value (AOV)","https://pixis-brand-web-1dfin.sevalla.page/glossary/average-order-value-aov/","average-order-value-aov",[1770],{"fullName":371,"asset":1771,"position":419,"bio":9,"linkedIn":9,"authorPage":1776},[1772],{"type":27,"image":1773,"mobileImage":1775},[1774],{"src":417,"alt":9},[],[],{"title":1778,"description":382,"advanced":1779,"keywords":1781,"social":1782},"Average Order Value (AOV) | Pixis",{"canonical":9,"robots":1780},[],[],{"facebook":1783,"twitter":1784},{"description":382,"title":1778},{"description":382,"title":1778},[1786],{"title":526,"slug":527},[1788],{"blocks":1789},[1790],{"type":437,"textBlock":1791},"\u003Cspan style=\"font-weight:400;\">Average order value (AOV) measures the average amount of money a customer spends in a single transaction with a business. It is a key performance indicator (KPI) in e-commerce and retail that helps businesses understand purchasing behavior and evaluate the effectiveness of strategies to increase revenue per order.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">AOV is calculated by dividing total revenue by the number of orders over a specific time period. For example, if a business generates $10,000 in revenue from 200 orders in a month, the AOV would be $50. This metric is crucial because it reveals how much customers are spending per transaction.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">By monitoring AOV, businesses can assess the impact of promotions, upselling, and cross-selling tactics. Increasing AOV is often more cost-effective than acquiring new customers, as businesses can generate more revenue from existing customers.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, an online clothing retailer might bundle complementary items or offer free shipping on orders over a certain amount to encourage customers to spend more.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Businesses use several strategies to increase AOV, including:\u003C/span>\n\u003Cul>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Upselling\u003C/b>\u003Cspan style=\"font-weight:400;\">: Encouraging customers to purchase higher-priced items or premium versions of products.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Cross-selling\u003C/b>\u003Cspan style=\"font-weight:400;\">: Recommending related products to be purchased together, such as accessories for electronics.\u003C/span>\u003C/li>\n \t\u003Cli style=\"font-weight:400;\">\u003Cb>Incentive Offers\u003C/b>\u003Cspan style=\"font-weight:400;\">: Providing discounts or free shipping on orders that exceed a minimum threshold.\u003C/span>\u003C/li>\n\u003C/ul>\n\u003Cspan style=\"font-weight:400;\">AOV analysis can also inform product pricing, inventory management, and marketing campaigns. Businesses that identify trends in AOV can better allocate resources to maximize profitability.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">A high AOV can significantly increase revenue without the need to acquire more customers. Businesses that successfully encourage customers to buy more items or higher-value products benefit from improved margins and operational efficiency. Tracking AOV also helps businesses identify which products or strategies drive the most value.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Additionally, AOV is closely tied to customer lifetime value (CLV), making it an essential metric for long-term business growth.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">E-commerce platforms often display product recommendations to increase AOV. For example, a beauty retailer might suggest add-on items like makeup brushes alongside a foundation purchase. Subscription services use AOV to optimize package tiers by bundling services and add-ons to boost transaction value.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Retailers also analyze AOV trends during promotional campaigns to determine which strategies yield the highest returns.\u003C/span>",{"uri":1793,"id":1794,"title":1795,"url":1796,"postDate":1797,"dateUpdated":375,"slug":1798,"sectionHandle":373,"type":410,"authors":1799,"seo":1807,"categories":1815,"contentArea":1817,"siteName":371},"glossary/backpropagation","17731","Backpropagation","https://pixis-brand-web-1dfin.sevalla.page/glossary/backpropagation/","2025-03-06T07:01:17-05:00","backpropagation",[1800],{"fullName":371,"asset":1801,"position":419,"bio":9,"linkedIn":9,"authorPage":1806},[1802],{"type":27,"image":1803,"mobileImage":1805},[1804],{"src":417,"alt":9},[],[],{"title":1808,"description":382,"advanced":1809,"keywords":1811,"social":1812},"Backpropagation | Pixis",{"canonical":9,"robots":1810},[],[],{"facebook":1813,"twitter":1814},{"description":382,"title":1808},{"description":382,"title":1808},[1816],{"title":1308,"slug":1309},[1818],{"blocks":1819},[1820],{"type":437,"textBlock":1821},"Backpropagation is crucial in training artificial neural networks to learn and improve their performance over time. The basic idea behind backpropagation is to propagate the error of the output back through the network, to let it adjust itself (learn) in a way that reduces the error in the future. It is a key component of many popular applications, including image and speech recognition, natural language processing, and financial modeling. Pixis AIs use backpropagation to decrease error rates and make better recommendations for improved efficiency.",{"uri":1823,"id":1824,"title":1825,"url":1826,"postDate":753,"dateUpdated":1827,"slug":1828,"sectionHandle":373,"type":410,"authors":1829,"seo":1837,"categories":1845,"contentArea":1847,"siteName":371},"glossary/behavioral-signals","17479","Behavioral Signals","https://pixis-brand-web-1dfin.sevalla.page/glossary/behavioral-signals/","2025-04-17T03:17:17-04:00","behavioral-signals",[1830],{"fullName":371,"asset":1831,"position":419,"bio":9,"linkedIn":9,"authorPage":1836},[1832],{"type":27,"image":1833,"mobileImage":1835},[1834],{"src":417,"alt":9},[],[],{"title":1838,"description":382,"advanced":1839,"keywords":1841,"social":1842},"Behavioral Signals | Pixis",{"canonical":9,"robots":1840},[],[],{"facebook":1843,"twitter":1844},{"description":382,"title":1838},{"description":382,"title":1838},[1846],{"title":526,"slug":527},[1848],{"blocks":1849},[1850],{"type":437,"textBlock":1851},"\u003Cspan style=\"font-weight:400;\">Behavioral signals refer to data points that capture how users interact with a website, app, or digital platform. These signals provide insight into user intent and engagement, helping businesses tailor their marketing and product strategies to meet customer needs.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Behavioral signals include actions such as clicks, scroll depth, time spent on a page, product views, and purchases. Each action reveals information about a user’s level of interest and decision-making process. For instance, a user who spends several minutes on a product page but does not complete a purchase may be hesitant due to price or lack of product information.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Businesses use behavioral data to segment users based on their engagement levels. High-value signals, such as adding items to a cart, suggest strong purchase intent, while low-value signals, such as brief visits to a landing page, may indicate casual browsing.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Digital platforms track behavioral data through cookies, session tracking, and analytics tools. AI and machine learning models analyze this data to identify patterns in user behavior. These insights inform marketing strategies, such as retargeting campaigns or personalized recommendations.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, a video streaming platform might track watch history and use that data to recommend shows based on a user’s preferences. Similarly, e-commerce platforms analyze browsing behavior to suggest related products.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Behavioral signals improve marketing effectiveness by enabling businesses to deliver relevant messages at the right time. Personalized experiences increase user engagement and conversion rates. Behavioral insights also help businesses identify areas of friction in the customer journey, such as pages where users frequently drop off.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">In addition, behavioral data supports advanced segmentation, allowing marketers to create targeted campaigns that cater to specific user needs and preferences.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">E-commerce platforms use behavioral signals to power personalized product recommendations and abandoned cart recovery campaigns. Behavioral data also informs customer support initiatives by identifying users who may need assistance based on their interactions.\u003C/span>",{"uri":1853,"id":1854,"title":1855,"url":1856,"postDate":1857,"dateUpdated":1858,"slug":1859,"sectionHandle":373,"type":410,"authors":1860,"seo":1868,"categories":1876,"contentArea":1878,"siteName":371},"glossary/bert","17737","BERT","https://pixis-brand-web-1dfin.sevalla.page/glossary/bert/","2025-03-06T07:01:49-05:00","2025-04-17T03:17:38-04:00","bert",[1861],{"fullName":371,"asset":1862,"position":419,"bio":9,"linkedIn":9,"authorPage":1867},[1863],{"type":27,"image":1864,"mobileImage":1866},[1865],{"src":417,"alt":9},[],[],{"title":1869,"description":382,"advanced":1870,"keywords":1872,"social":1873},"BERT | Pixis",{"canonical":9,"robots":1871},[],[],{"facebook":1874,"twitter":1875},{"description":382,"title":1869},{"description":382,"title":1869},[1877],{"title":1308,"slug":1309},[1879],{"blocks":1880},[1881],{"type":437,"textBlock":1882},"BERT is a powerful AI model that is designed to understand and generate natural language. It is widely used in a variety of Natural Language Processing (NLP) tasks such as accurately predicting the next word in a sentence, identifying the main topic of a piece of text, or summarizing a long document. It is used to perform tasks related to NLP, such as language translation, text summarization, and question-answering, at scale with speed. Pixis uses BERT to facilitate the generation of contextual communication for our customers.",{"uri":1884,"id":1885,"title":1886,"url":1887,"postDate":1888,"dateUpdated":1858,"slug":1889,"sectionHandle":373,"type":410,"authors":1890,"seo":1898,"categories":1906,"contentArea":1908,"siteName":371},"glossary/black-box","17743","Black Box","https://pixis-brand-web-1dfin.sevalla.page/glossary/black-box/","2025-03-06T07:02:20-05:00","black-box",[1891],{"fullName":371,"asset":1892,"position":419,"bio":9,"linkedIn":9,"authorPage":1897},[1893],{"type":27,"image":1894,"mobileImage":1896},[1895],{"src":417,"alt":9},[],[],{"title":1899,"description":382,"advanced":1900,"keywords":1902,"social":1903},"Black Box | Pixis",{"canonical":9,"robots":1901},[],[],{"facebook":1904,"twitter":1905},{"description":382,"title":1899},{"description":382,"title":1899},[1907],{"title":1308,"slug":1309},[1909],{"blocks":1910},[1911],{"type":437,"textBlock":1912},"\u003Cspan style=\"font-weight:400;\">Black Box artificial intelligence and machine learning refers to a system or algorithm whose internal workings are not transparent or easily understandable to the user or observer. In other words, the input-output behavior of the system is known, but the internal processes and decision-making mechanisms remain opaque.\u003C/span>",{"uri":1914,"id":1915,"title":1916,"url":1917,"postDate":753,"dateUpdated":1827,"slug":1918,"sectionHandle":373,"type":410,"authors":1919,"seo":1927,"categories":1935,"contentArea":1937,"siteName":371},"glossary/buying-journey","17485","Buying Journey","https://pixis-brand-web-1dfin.sevalla.page/glossary/buying-journey/","buying-journey",[1920],{"fullName":371,"asset":1921,"position":419,"bio":9,"linkedIn":9,"authorPage":1926},[1922],{"type":27,"image":1923,"mobileImage":1925},[1924],{"src":417,"alt":9},[],[],{"title":1928,"description":382,"advanced":1929,"keywords":1931,"social":1932},"Buying Journey | Pixis",{"canonical":9,"robots":1930},[],[],{"facebook":1933,"twitter":1934},{"description":382,"title":1928},{"description":382,"title":1928},[1936],{"title":526,"slug":527},[1938],{"blocks":1939},[1940],{"type":437,"textBlock":1941},"\u003Cspan style=\"font-weight:400;\">The buying journey, also known as the customer journey, refers to the process customers go through from becoming aware of a product to making a purchase. It typically includes several stages: awareness, consideration, decision, and post-purchase.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Customers rarely make instant decisions to purchase a product. Instead, they progress through stages where they evaluate their needs, research solutions, compare options, and decide on a purchase. Businesses that understand the buying journey can provide the right information and support at each stage to guide customers toward conversion.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, during the awareness stage, potential customers might encounter a product through social media ads. In the consideration stage, they may compare features and prices on multiple websites. By the decision stage, they are evaluating reviews and promotions before making a purchase.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Mapping the buying journey helps businesses identify touchpoints where they can influence customer decisions.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Businesses gather data on customer behavior at each stage of the journey. Analytics tools track user interactions, such as page views, product comparisons, and purchases. Marketing teams use this data to create content and campaigns tailored to each stage.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, a business might use educational blog posts to attract customers in the awareness stage and offer product demos to those in the consideration stage.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">A well-structured buying journey enhances the customer experience by delivering relevant information and support at the right moments. This approach increases the likelihood of conversion and builds trust with customers. It also allows businesses to identify bottlenecks where users may drop off, enabling them to optimize their sales funnel.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">E-commerce companies map the buying journey to improve their product discovery and checkout processes. Digital platforms create personalized user flows that guide customers toward desired actions, such as signing up for services or completing purchases.\u003C/span>",{"uri":1943,"id":1944,"title":1945,"url":1946,"postDate":753,"dateUpdated":1947,"slug":1948,"sectionHandle":373,"type":410,"authors":1949,"seo":1957,"categories":1965,"contentArea":1967,"siteName":371},"glossary/churn","17491","Churn","https://pixis-brand-web-1dfin.sevalla.page/glossary/churn/","2025-04-17T03:17:18-04:00","churn",[1950],{"fullName":371,"asset":1951,"position":419,"bio":9,"linkedIn":9,"authorPage":1956},[1952],{"type":27,"image":1953,"mobileImage":1955},[1954],{"src":417,"alt":9},[],[],{"title":1958,"description":382,"advanced":1959,"keywords":1961,"social":1962},"Churn | Pixis",{"canonical":9,"robots":1960},[],[],{"facebook":1963,"twitter":1964},{"description":382,"title":1958},{"description":382,"title":1958},[1966],{"title":526,"slug":527},[1968],{"blocks":1969},[1970],{"type":437,"textBlock":1971},"\u003Cspan style=\"font-weight:400;\">Churn refers to the rate at which customers stop doing business with a company. It is a critical metric for subscription-based businesses and industries where customer retention drives profitability.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Churn can be categorized into voluntary churn (customers who cancel their subscriptions or stop buying) and involuntary churn (customers lost due to failed payments or account issues). High churn rates indicate dissatisfaction or a failure to meet customer needs.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Businesses aim to reduce churn by improving product quality, customer service, and engagement. Identifying the reasons behind churn helps companies implement strategies to retain at-risk customers.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Churn rate is calculated by dividing the number of customers lost during a period by the total number of customers at the start of that period. Analytics tools track customer behavior to detect warning signs, such as reduced engagement or complaints.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Businesses often deploy proactive measures, such as targeted retention offers, to prevent churn. Customer feedback surveys also provide insights into why users leave.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Reducing churn increases customer lifetime value (CLV) and overall profitability. Retaining customers is generally more cost-effective than acquiring new ones. By addressing the causes of churn, businesses can improve their products and services, leading to greater long-term success.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Subscription services monitor churn to identify trends and take corrective action. E-commerce businesses also analyze repeat purchase behavior to maintain customer loyalty and reduce attrition.\u003C/span>",{"uri":1973,"id":1974,"title":1975,"url":1976,"postDate":1977,"dateUpdated":1978,"slug":1979,"sectionHandle":373,"type":410,"authors":1980,"seo":1988,"categories":1996,"contentArea":1998,"siteName":371},"glossary/clarity-scoring","17779","Clarity Scoring","https://pixis-brand-web-1dfin.sevalla.page/glossary/clarity-scoring/","2025-03-06T07:14:35-05:00","2025-04-17T03:17:41-04:00","clarity-scoring",[1981],{"fullName":371,"asset":1982,"position":419,"bio":9,"linkedIn":9,"authorPage":1987},[1983],{"type":27,"image":1984,"mobileImage":1986},[1985],{"src":417,"alt":9},[],[],{"title":1989,"description":382,"advanced":1990,"keywords":1992,"social":1993},"Clarity Scoring | Pixis",{"canonical":9,"robots":1991},[],[],{"facebook":1994,"twitter":1995},{"description":382,"title":1989},{"description":382,"title":1989},[1997],{"title":1308,"slug":1309},[1999],{"blocks":2000},[2001],{"type":437,"textBlock":2002},"Clarity Scoring, also known as readability scoring or readability assessment, is a process of evaluating the readability of written text using AI algorithms, with the goal of identifying and improving the clarity and simplicity of the text. There are several different measures of readability that can be used, each of which takes into account different aspects of the text such as the length of sentences, the complexity of the vocabulary, and the use of technical terms. Clarity Scoring algorithms use these measures to assign a score to a piece of text, indicating how easy or difficult it is to understand.",{"uri":2004,"id":2005,"title":2006,"url":2007,"postDate":2008,"dateUpdated":2009,"slug":2010,"sectionHandle":373,"type":410,"authors":2011,"seo":2019,"categories":2027,"contentArea":2029,"siteName":371},"glossary/codeless-ai","17749","Codeless AI","https://pixis-brand-web-1dfin.sevalla.page/glossary/codeless-ai/","2025-03-06T07:03:15-05:00","2025-04-17T03:17:39-04:00","codeless-ai",[2012],{"fullName":371,"asset":2013,"position":419,"bio":9,"linkedIn":9,"authorPage":2018},[2014],{"type":27,"image":2015,"mobileImage":2017},[2016],{"src":417,"alt":9},[],[],{"title":2020,"description":382,"advanced":2021,"keywords":2023,"social":2024},"Codeless AI | Pixis",{"canonical":9,"robots":2022},[],[],{"facebook":2025,"twitter":2026},{"description":382,"title":2020},{"description":382,"title":2020},[2028],{"title":1308,"slug":1309},[2030],{"blocks":2031},[2032],{"type":437,"textBlock":2033},"Codeless AI refers to Artificial Intelligence (AI) technologies and products that do not require users to have programming skills or knowledge of AI algorithms in order to use them. They are specifically designed to be accessible to a wide range of users, regardless of their technical expertise. Codeless AI tools typically offer a graphical user interface (GUI) or other intuitive interfaces that allow users to input data, set parameters, and visualize results without having to write code. A great example of this are the Pixis codeless AI playgrounds that make it possible for customers to use advanced AI capabilities in their day-to-day marketing and demand generation functions without the need for specialized programming skills.",{"uri":2035,"id":2036,"title":2037,"url":2038,"postDate":2039,"dateUpdated":2040,"slug":2041,"sectionHandle":373,"type":410,"authors":2042,"seo":2050,"categories":2058,"contentArea":2060,"siteName":371},"glossary/confidence-score","17761","Confidence Score","https://pixis-brand-web-1dfin.sevalla.page/glossary/confidence-score/","2025-03-06T07:12:34-05:00","2025-04-17T03:17:40-04:00","confidence-score",[2043],{"fullName":371,"asset":2044,"position":419,"bio":9,"linkedIn":9,"authorPage":2049},[2045],{"type":27,"image":2046,"mobileImage":2048},[2047],{"src":417,"alt":9},[],[],{"title":2051,"description":382,"advanced":2052,"keywords":2054,"social":2055},"Confidence Score | Pixis",{"canonical":9,"robots":2053},[],[],{"facebook":2056,"twitter":2057},{"description":382,"title":2051},{"description":382,"title":2051},[2059],{"title":1308,"slug":1309},[2061],{"blocks":2062},[2063],{"type":437,"textBlock":2064},"A Confidence Score is a measure of the reliability or certainty of a prediction or assessment made by a machine learning model or other automated systems. It is typically expressed as a probability or as a percentage and reflects the degree of confidence that the underlying model has in its prediction or assessment. For example, if a machine learning model is trained to classify images as either \"cat\" or \"not cat,\" and it predicts that a particular image is a cat with a confidence score of 95%, this means that the model is 95% confident that the image is a cat. On the other hand, if the model predicts that the image is a cat with a confidence score of 50%, this means that the model is less certain of its prediction, and there is a higher likelihood of error.\n\nThe Confidence Score is typically used by a human user to make informed decisions based on machine or AI recommendations.",{"uri":2066,"id":2067,"title":2068,"url":2069,"postDate":2070,"dateUpdated":2071,"slug":2072,"sectionHandle":373,"type":410,"authors":2073,"seo":2081,"categories":2089,"contentArea":2091,"siteName":371},"glossary/content-intelligence","17785","Content Intelligence","https://pixis-brand-web-1dfin.sevalla.page/glossary/content-intelligence/","2025-03-06T07:14:58-05:00","2025-04-17T03:17:42-04:00","content-intelligence",[2074],{"fullName":371,"asset":2075,"position":419,"bio":9,"linkedIn":9,"authorPage":2080},[2076],{"type":27,"image":2077,"mobileImage":2079},[2078],{"src":417,"alt":9},[],[],{"title":2082,"description":382,"advanced":2083,"keywords":2085,"social":2086},"Content Intelligence | Pixis",{"canonical":9,"robots":2084},[],[],{"facebook":2087,"twitter":2088},{"description":382,"title":2082},{"description":382,"title":2082},[2090],{"title":1308,"slug":1309},[2092],{"blocks":2093},[2094],{"type":437,"textBlock":2095},"Content intelligence is a field of Artificial Intelligence (AI) that focuses on extracting insights, knowledge, and meaning from large volumes of content, such as text, audio, or video. It involves the use of AI techniques, such as Natural Language Processing (NLP), machine learning, and text analytics, to analyze and understand the content, and extract valuable information from it.\n\nFor example, Pixis uses Content Intelligence to analyze and identify trends and patterns in large datasets, with the goal of enabling organizations to gain a better understanding of their content and to use this understanding to make informed decisions, improve processes, and drive business value.",{"uri":2097,"id":2098,"title":2099,"url":2100,"postDate":2101,"dateUpdated":2009,"slug":2102,"sectionHandle":373,"type":410,"authors":2103,"seo":2111,"categories":2119,"contentArea":2121,"siteName":371},"glossary/contextual-ai-models","17755","Contextual AI Models","https://pixis-brand-web-1dfin.sevalla.page/glossary/contextual-ai-models/","2025-03-06T07:11:56-05:00","contextual-ai-models",[2104],{"fullName":371,"asset":2105,"position":419,"bio":9,"linkedIn":9,"authorPage":2110},[2106],{"type":27,"image":2107,"mobileImage":2109},[2108],{"src":417,"alt":9},[],[],{"title":2112,"description":382,"advanced":2113,"keywords":2115,"social":2116},"Contextual AI Models | Pixis",{"canonical":9,"robots":2114},[],[],{"facebook":2117,"twitter":2118},{"description":382,"title":2112},{"description":382,"title":2112},[2120],{"title":1308,"slug":1309},[2122],{"blocks":2123},[2124],{"type":437,"textBlock":2125},"Contextual AI Models are Artificial Intelligence (AI) models that are able to take into account the context in which they are operating in order to provide more accurate and relevant responses to tasks or requests. For example, consider the word \"bat.\" Depending on the context, \"bat\" could refer to a flying mammal, a wooden club used in sports, or the act of hitting a ball with a bat. A contextual AI model would be able to understand the correct meaning of \"bat\" in each of these different contexts, based on the other words and phrases that appear alongside it.",{"uri":2127,"id":2128,"title":2129,"url":2130,"postDate":753,"dateUpdated":1947,"slug":2131,"sectionHandle":373,"type":410,"authors":2132,"seo":2140,"categories":2148,"contentArea":2150,"siteName":371},"glossary/conversion-rate","17497","Conversion Rate","https://pixis-brand-web-1dfin.sevalla.page/glossary/conversion-rate/","conversion-rate",[2133],{"fullName":371,"asset":2134,"position":419,"bio":9,"linkedIn":9,"authorPage":2139},[2135],{"type":27,"image":2136,"mobileImage":2138},[2137],{"src":417,"alt":9},[],[],{"title":2141,"description":382,"advanced":2142,"keywords":2144,"social":2145},"Conversion Rate | Pixis",{"canonical":9,"robots":2143},[],[],{"facebook":2146,"twitter":2147},{"description":382,"title":2141},{"description":382,"title":2141},[2149],{"title":526,"slug":527},[2151],{"blocks":2152},[2153],{"type":437,"textBlock":2154},"\u003Cspan style=\"font-weight:400;\">Conversion rate measures the percentage of users who complete a desired action on a website, app, or marketing campaign. Common conversions include making a purchase, signing up for a newsletter, or submitting a contact form.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">A high conversion rate indicates that a marketing or sales strategy effectively drives users to take action. Businesses optimize conversion rates by improving user experience, refining messaging, and removing friction points in the customer journey.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, a landing page with clear calls to action and persuasive content will likely convert more visitors than a poorly designed page with vague instructions.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Conversion rate is calculated by dividing the number of conversions by the number of visitors or participants. Analytics platforms track user interactions and measure performance across channels, such as websites, emails, and ads.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Marketers use A/B testing to evaluate which elements improve conversion rates. They may test variations in page design, copy, or offers to determine the most effective approach.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Improving conversion rates leads to higher revenue without increasing marketing spend. By optimizing conversion points, businesses can maximize the value of their existing traffic. It also improves the customer experience and makes it easier for users to complete actions.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">E-commerce businesses focus on optimizing product pages and checkout flows to increase conversions. Lead generation campaigns use similar techniques to improve form submissions. Conversion rate is a key metric in virtually all digital marketing strategies.\u003C/span>",{"uri":2156,"id":2157,"title":2158,"url":2159,"postDate":753,"dateUpdated":2160,"slug":2161,"sectionHandle":373,"type":410,"authors":2162,"seo":2170,"categories":2178,"contentArea":2180,"siteName":371},"glossary/conversion-rate-optimization-cro","17503","Conversion Rate Optimization (CRO)","https://pixis-brand-web-1dfin.sevalla.page/glossary/conversion-rate-optimization-cro/","2025-04-17T03:17:19-04:00","conversion-rate-optimization-cro",[2163],{"fullName":371,"asset":2164,"position":419,"bio":9,"linkedIn":9,"authorPage":2169},[2165],{"type":27,"image":2166,"mobileImage":2168},[2167],{"src":417,"alt":9},[],[],{"title":2171,"description":382,"advanced":2172,"keywords":2174,"social":2175},"Conversion Rate Optimization (CRO) | Pixis",{"canonical":9,"robots":2173},[],[],{"facebook":2176,"twitter":2177},{"description":382,"title":2171},{"description":382,"title":2171},[2179],{"title":526,"slug":527},[2181],{"blocks":2182},[2183],{"type":437,"textBlock":2184},"\u003Cspan style=\"font-weight:400;\">Conversion Rate Optimization (CRO) is the process of improving a website, app, or marketing campaign to increase the percentage of users who complete a desired action. These actions, or conversions, can include making a purchase, signing up for a service, or filling out a form. CRO focuses on removing barriers in the user experience that prevent conversions, helping businesses achieve better results without increasing traffic.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">CRO aims to maximize the value of existing traffic by improving usability, content, and design to encourage users to take action. A low conversion rate often points to issues such as unclear calls to action, lengthy forms, or slow page loading times. CRO strategies address these problems through testing and iterative improvements.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, an e-commerce store may improve conversions by simplifying the checkout process or providing more trust signals, such as customer reviews and secure payment badges. By continually refining user interactions, businesses can create smoother pathways for users to achieve their goals.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">CRO does not follow a one-size-fits-all approach. Effective strategies vary depending on factors like target audience, business model, and platform.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Conversion Rate Optimization begins with data collection. Analytics tools track key user actions and identify pages or features where users drop off. Once problem areas are identified, marketers form hypotheses about what changes might improve performance. A/B testing is often used to evaluate variations.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, a CRO test might compare two versions of a product page. One version highlights customer testimonials, while the other emphasizes a limited-time offer. After measuring results, marketers implement the version that delivers better conversion rates.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">CRO improves return on investment (ROI) by increasing conversions without requiring more traffic or additional ad spend. Optimizing conversion points leads to higher revenue and improved customer satisfaction. By removing friction from the user experience, businesses reduce bounce rates and improve engagement.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">E-commerce stores optimize product pages and checkout flows to improve sales conversions. Lead generation websites refine form designs to encourage more sign-ups.\u003C/span>",{"uri":2186,"id":2187,"title":2188,"url":2189,"postDate":2190,"dateUpdated":2071,"slug":2191,"sectionHandle":373,"type":410,"authors":2192,"seo":2200,"categories":2208,"contentArea":2210,"siteName":371},"glossary/convolutional-neural-networks","17791","Convolutional Neural Networks","https://pixis-brand-web-1dfin.sevalla.page/glossary/convolutional-neural-networks/","2025-03-06T07:15:23-05:00","convolutional-neural-networks",[2193],{"fullName":371,"asset":2194,"position":419,"bio":9,"linkedIn":9,"authorPage":2199},[2195],{"type":27,"image":2196,"mobileImage":2198},[2197],{"src":417,"alt":9},[],[],{"title":2201,"description":382,"advanced":2202,"keywords":2204,"social":2205},"Convolutional Neural Networks | Pixis",{"canonical":9,"robots":2203},[],[],{"facebook":2206,"twitter":2207},{"description":382,"title":2201},{"description":382,"title":2201},[2209],{"title":1308,"slug":1309},[2211],{"blocks":2212},[2213],{"type":437,"textBlock":2214},"Convolutional Neural Networks (CNNs) are a type of artificial neural network which are tasked with analyzing and understanding complex data for a wide range of applications, including image and video analysis, Natural Language Processing (NLP), object detection, and face recognition.",{"uri":2216,"id":2217,"title":2218,"url":2219,"postDate":2220,"dateUpdated":2040,"slug":2221,"sectionHandle":373,"type":410,"authors":2222,"seo":2230,"categories":2238,"contentArea":2240,"siteName":371},"glossary/cosine-similarity","17767","Cosine Similarity","https://pixis-brand-web-1dfin.sevalla.page/glossary/cosine-similarity/","2025-03-06T07:13:12-05:00","cosine-similarity",[2223],{"fullName":371,"asset":2224,"position":419,"bio":9,"linkedIn":9,"authorPage":2229},[2225],{"type":27,"image":2226,"mobileImage":2228},[2227],{"src":417,"alt":9},[],[],{"title":2231,"description":382,"advanced":2232,"keywords":2234,"social":2235},"Cosine Similarity | Pixis",{"canonical":9,"robots":2233},[],[],{"facebook":2236,"twitter":2237},{"description":382,"title":2231},{"description":382,"title":2231},[2239],{"title":1308,"slug":1309},[2241],{"blocks":2242},[2243],{"type":437,"textBlock":2244},"Cosine Similarity is a measure of similarity between two data sets. It is commonly used in information retrieval, recommendation systems, and other areas where it is necessary to compare the similarity of two documents or items. This is relatively robust to the effects of scaling, translation, and rotation. For example, in the case of textual data, cosine similarity can be used to find the similarity of texts in the document.",{"uri":2246,"id":2247,"title":2248,"url":2249,"postDate":753,"dateUpdated":2160,"slug":2250,"sectionHandle":373,"type":410,"authors":2251,"seo":2259,"categories":2267,"contentArea":2269,"siteName":371},"glossary/cost-per-conversion","17509","Cost Per Conversion","https://pixis-brand-web-1dfin.sevalla.page/glossary/cost-per-conversion/","cost-per-conversion",[2252],{"fullName":371,"asset":2253,"position":419,"bio":9,"linkedIn":9,"authorPage":2258},[2254],{"type":27,"image":2255,"mobileImage":2257},[2256],{"src":417,"alt":9},[],[],{"title":2260,"description":382,"advanced":2261,"keywords":2263,"social":2264},"Cost Per Conversion | Pixis",{"canonical":9,"robots":2262},[],[],{"facebook":2265,"twitter":2266},{"description":382,"title":2260},{"description":382,"title":2260},[2268],{"title":526,"slug":527},[2270],{"blocks":2271},[2272],{"type":437,"textBlock":2273},"\u003Cspan style=\"font-weight:400;\">Cost per conversion (CPC) is a metric that measures how much a business spends to acquire a single conversion. This conversion can be any desired action, such as a sale, lead submission, or app download. Cost per conversion helps businesses assess the efficiency of their marketing campaigns and determine how effectively their ad spend drives results.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Marketers calculate cost per conversion by dividing the total ad spend by the number of conversions generated. For example, if a campaign spends $1,000 and results in 50 conversions, the cost per conversion is $20. This metric is important because it shows whether marketing efforts are yielding a positive return on investment (ROI).\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Low cost per conversion typically indicates a well-optimized campaign, while a high cost suggests that improvements may be needed in areas such as targeting, ad creatives, or landing pages. Businesses often compare CPC across different campaigns and channels to identify the most cost-effective strategies.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Marketing platforms like Google Ads and Meta Ads track conversions and calculate CPC automatically. To optimize this metric, businesses may adjust their ad targeting criteria, change bidding strategies, or refine creative assets. For example, a business might lower CPC by narrowing its audience to users who have shown strong intent, such as those who previously interacted with the brand.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Effective optimization requires regular performance monitoring. Marketers review data to identify which campaigns or keywords are delivering the lowest cost per conversion and reallocate budgets accordingly.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Monitoring cost per conversion ensures that businesses allocate their marketing budgets efficiently. By identifying high-performing campaigns, businesses can maximize their ROI. Understanding CPC also helps marketers balance short-term campaign costs with long-term customer value.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">E-commerce businesses use CPC to assess the effectiveness of product-specific campaigns. In digital advertising, CPC informs bidding strategies for pay-per-click (PPC) platforms like Google Ads and Meta Ads.\u003C/span>",{"uri":2275,"id":2276,"title":2277,"url":2278,"postDate":2279,"dateUpdated":1978,"slug":2280,"sectionHandle":373,"type":410,"authors":2281,"seo":2289,"categories":2297,"contentArea":2299,"siteName":371},"glossary/creative-adversarial-network","17773","Creative Adversarial Network","https://pixis-brand-web-1dfin.sevalla.page/glossary/creative-adversarial-network/","2025-03-06T07:14:04-05:00","creative-adversarial-network",[2282],{"fullName":371,"asset":2283,"position":419,"bio":9,"linkedIn":9,"authorPage":2288},[2284],{"type":27,"image":2285,"mobileImage":2287},[2286],{"src":417,"alt":9},[],[],{"title":2290,"description":382,"advanced":2291,"keywords":2293,"social":2294},"Creative Adversarial Network | Pixis",{"canonical":9,"robots":2292},[],[],{"facebook":2295,"twitter":2296},{"description":382,"title":2290},{"description":382,"title":2290},[2298],{"title":1308,"slug":1309},[2300],{"blocks":2301},[2302],{"type":437,"textBlock":2303},"A Creative Adversarial Network (CAN) is a type of Artificial Intelligence (AI) system that generates original content in a specific domain, such as text, images, or music. It is called a \"creative\" adversarial network because it uses a type of machine learning called adversarial training, in which two AI models are trained to work together and compete against each other in order to generate high-quality content. In a CAN, one model called the \"generator,\" is responsible for generating new content, while the other model, called the \"discriminator,\" is responsible for evaluating the quality of the content and determining whether it is original or not. Simply put, it uses a combination of machine learning techniques and adversarial training to generate new and creative content that is similar to the training data, but not identical and may contain novel elements or variations.",{"uri":2305,"id":2306,"title":2307,"url":2308,"postDate":753,"dateUpdated":2309,"slug":2310,"sectionHandle":373,"type":410,"authors":2311,"seo":2319,"categories":2327,"contentArea":2329,"siteName":371},"glossary/cross-channel-marketing","17515","Cross-Channel Marketing","https://pixis-brand-web-1dfin.sevalla.page/glossary/cross-channel-marketing/","2025-04-17T03:17:20-04:00","cross-channel-marketing",[2312],{"fullName":371,"asset":2313,"position":419,"bio":9,"linkedIn":9,"authorPage":2318},[2314],{"type":27,"image":2315,"mobileImage":2317},[2316],{"src":417,"alt":9},[],[],{"title":2320,"description":382,"advanced":2321,"keywords":2323,"social":2324},"Cross-Channel Marketing | Pixis",{"canonical":9,"robots":2322},[],[],{"facebook":2325,"twitter":2326},{"description":382,"title":2320},{"description":382,"title":2320},[2328],{"title":526,"slug":527},[2330],{"blocks":2331},[2332],{"type":437,"textBlock":2333},"\u003Cspan style=\"font-weight:400;\">Cross-channel marketing is a strategy where businesses engage with customers across multiple platforms and channels in a coordinated manner. These channels may include email, social media, websites, mobile apps, and physical stores. The goal is to create a consistent experience that reinforces messaging and builds trust throughout the customer journey.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Customers today interact with brands on various platforms before making a purchase decision. They might start by discovering a product through a social media ad, research it on a website, and then receive follow-up emails with personalized offers. Cross-channel marketing ensures that these interactions are seamless and consistent.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Effective cross-channel marketing requires alignment between departments such as marketing, sales, and customer support. Messaging, offers, and branding must remain consistent while being tailored to the unique features of each channel.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, a company might use engaging visuals on Instagram to raise awareness, send email newsletters with product recommendations, and offer in-app discounts for loyal customers.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Businesses use marketing automation platforms to manage campaigns across multiple channels. These platforms track user interactions and segment audiences based on behavior. Campaigns are then customized for each platform, ensuring that customers receive relevant messages without redundancy.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Cross-channel marketing often involves personalized touchpoints that guide users through the buying journey. For instance, users who abandon their shopping cart on a website might receive a reminder email followed by a targeted ad on social media.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Cross-channel marketing improves brand visibility and engagement by reaching customers where they spend the most time. Consistent messaging across platforms builds trust and reinforces brand identity. Businesses also benefit from improved conversion rates, as users are more likely to take action when they encounter coordinated marketing efforts.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Additionally, cross-channel strategies provide a holistic view of customer behavior, allowing businesses to optimize touchpoints and maximize campaign effectiveness.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Retail brands use cross-channel marketing to promote products through email, social ads, and in-store events. E-commerce platforms integrate multiple channels to provide seamless shopping experiences that boost customer loyalty.\u003C/span>",{"uri":2335,"id":2336,"title":2337,"url":2338,"postDate":2339,"dateUpdated":2340,"slug":2341,"sectionHandle":373,"type":410,"authors":2342,"seo":2350,"categories":2358,"contentArea":2360,"siteName":371},"glossary/cross-channel-marketing-automation","17533","Cross-Channel Marketing Automation","https://pixis-brand-web-1dfin.sevalla.page/glossary/cross-channel-marketing-automation/","2025-03-12T16:27:12-04:00","2025-04-17T03:17:21-04:00","cross-channel-marketing-automation",[2343],{"fullName":371,"asset":2344,"position":419,"bio":9,"linkedIn":9,"authorPage":2349},[2345],{"type":27,"image":2346,"mobileImage":2348},[2347],{"src":417,"alt":9},[],[],{"title":2351,"description":382,"advanced":2352,"keywords":2354,"social":2355},"Cross-Channel Marketing Automation | Pixis",{"canonical":9,"robots":2353},[],[],{"facebook":2356,"twitter":2357},{"description":382,"title":2351},{"description":382,"title":2351},[2359],{"title":526,"slug":527},[2361],{"blocks":2362},[2363],{"type":437,"textBlock":2364},"\u003Cspan style=\"font-weight:400;\">Cross-channel marketing automation refers to the use of technology to streamline marketing activities across multiple platforms. This strategy allows businesses to manage campaigns, deliver messages, and track user interactions on channels such as email, social media, mobile apps, and websites through a unified platform.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Manually coordinating marketing efforts across multiple channels can lead to inconsistent messaging and inefficient resource allocation. Marketing automation solves this by enabling marketers to automate repetitive tasks like email scheduling, social media posts, and ad placement while maintaining consistency across platforms. Automation also centralizes data collection, providing a holistic view of customer behavior.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, if a user interacts with a brand’s email campaign, the system can automatically trigger follow-up actions, such as personalized product recommendations on social media. Automation tools help businesses deliver a seamless experience without overwhelming marketing teams with manual tasks.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Marketing automation platforms collect user behavior data and segment audiences based on their actions. Predefined workflows guide how and when messages are sent. For example, a business might set up a campaign where users who abandon their carts receive an email reminder, followed by a retargeting ad on Facebook.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">The system tracks engagement metrics, allowing marketers to analyze performance and adjust campaigns in real-time.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Automation reduces the time and effort required to manage cross-channel campaigns. By delivering timely, relevant messages, businesses increase engagement and conversions. Automation also enhances personalization, as marketers can customize interactions based on user behavior and preferences.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Additionally, cross-channel marketing automation provides better visibility into the customer journey, making it easier to optimize touchpoints and maximize ROI.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Retailers use automation to synchronize product promotions across email, SMS, and social ads.\u003C/span>",{"uri":2366,"id":2367,"title":2368,"url":2369,"postDate":753,"dateUpdated":2309,"slug":2370,"sectionHandle":373,"type":410,"authors":2371,"seo":2379,"categories":2387,"contentArea":2389,"siteName":371},"glossary/cross-channel-messaging","17521","Cross-Channel Messaging","https://pixis-brand-web-1dfin.sevalla.page/glossary/cross-channel-messaging/","cross-channel-messaging",[2372],{"fullName":371,"asset":2373,"position":419,"bio":9,"linkedIn":9,"authorPage":2378},[2374],{"type":27,"image":2375,"mobileImage":2377},[2376],{"src":417,"alt":9},[],[],{"title":2380,"description":382,"advanced":2381,"keywords":2383,"social":2384},"Cross-Channel Messaging | Pixis",{"canonical":9,"robots":2382},[],[],{"facebook":2385,"twitter":2386},{"description":382,"title":2380},{"description":382,"title":2380},[2388],{"title":526,"slug":527},[2390],{"blocks":2391},[2392],{"type":437,"textBlock":2393},"\u003Cspan style=\"font-weight:400;\">Cross-channel messaging refers to delivering marketing messages across multiple platforms in a synchronized manner. It emphasizes consistency in tone, style, and information while tailoring content to the strengths of each channel. This approach enhances customer engagement by providing cohesive communication.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Customers expect a unified experience across touchpoints, whether they interact through a company’s website, app, or social media profiles. Cross-channel messaging ensures that customers receive relevant, timely messages without confusion or conflicting information.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">A well-executed strategy accounts for channel-specific behaviors. For example, social media posts may feature short, visually appealing content, while email newsletters include detailed product descriptions and offers. Despite these differences, the core message remains the same.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Businesses use customer data to segment audiences and customize messaging for each channel. Marketing automation platforms track user interactions and synchronize messaging schedules. For instance, users who visit a product page may receive follow-up messages through both email and SMS, reinforcing the call to action.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Marketers ensure that the message hierarchy is consistent, meaning customers are not overwhelmed by repeated or conflicting information.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Cross-channel messaging strengthens brand identity by maintaining consistent communication. It helps businesses reinforce important messages at multiple touchpoints, improving the chances of conversion. Personalized messages tailored to user behavior increase engagement and trust.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Additionally, this strategy provides insights into channel performance, allowing businesses to prioritize high-impact platforms.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Cross-channel messaging is essential for product launches and promotional campaigns. E-commerce brands use synchronized messages across email, social media, and mobile apps to drive sales.\u003C/span>",{"uri":2395,"id":2396,"title":2397,"url":2398,"postDate":753,"dateUpdated":2340,"slug":2399,"sectionHandle":373,"type":410,"authors":2400,"seo":2408,"categories":2416,"contentArea":2418,"siteName":371},"glossary/cross-sell","17527","Cross-Sell","https://pixis-brand-web-1dfin.sevalla.page/glossary/cross-sell/","cross-sell",[2401],{"fullName":371,"asset":2402,"position":419,"bio":9,"linkedIn":9,"authorPage":2407},[2403],{"type":27,"image":2404,"mobileImage":2406},[2405],{"src":417,"alt":9},[],[],{"title":2409,"description":382,"advanced":2410,"keywords":2412,"social":2413},"Cross-Sell | Pixis",{"canonical":9,"robots":2411},[],[],{"facebook":2414,"twitter":2415},{"description":382,"title":2409},{"description":382,"title":2409},[2417],{"title":526,"slug":527},[2419],{"blocks":2420},[2421],{"type":437,"textBlock":2422},"\u003Cspan style=\"font-weight:400;\">Cross-selling is a sales strategy where businesses recommend related or complementary products to customers. This encourages customers to purchase additional items, increasing the overall value of each transaction. Cross-selling enhances the customer experience by offering relevant product suggestions.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Cross-selling often occurs during the purchase process. For example, an electronics store might suggest accessories such as headphones or a protective case when a customer buys a smartphone. The goal is to increase average order value (AOV) and improve customer satisfaction by anticipating needs.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">This strategy differs from upselling, which involves encouraging customers to buy a more expensive version of the product they are considering.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Businesses analyze customer data to determine which products are commonly purchased together. Marketing platforms then display recommendations at key touchpoints, such as product pages or checkout screens. Sales representatives in physical stores also use cross-selling techniques by suggesting related items during conversations with customers.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Personalization plays a key role. Recommendations based on past purchases or browsing behavior are more likely to resonate with customers.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Cross-selling increases revenue by maximizing the value of each customer transaction. It also enhances the shopping experience by providing relevant suggestions, which can improve customer loyalty. Cross-selling strategies can reduce marketing costs, as businesses generate more sales from existing customers rather than relying solely on new customer acquisition.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">E-commerce platforms use cross-selling to recommend add-on products. Retailers implement cross-sell strategies through in-store promotions and bundled offers.\u003C/span>",{"uri":2424,"id":2425,"title":2426,"url":2427,"postDate":753,"dateUpdated":2340,"slug":2428,"sectionHandle":373,"type":410,"authors":2429,"seo":2437,"categories":2445,"contentArea":2447,"siteName":371},"glossary/customer-experience","17539","Customer Experience","https://pixis-brand-web-1dfin.sevalla.page/glossary/customer-experience/","customer-experience",[2430],{"fullName":371,"asset":2431,"position":419,"bio":9,"linkedIn":9,"authorPage":2436},[2432],{"type":27,"image":2433,"mobileImage":2435},[2434],{"src":417,"alt":9},[],[],{"title":2438,"description":382,"advanced":2439,"keywords":2441,"social":2442},"Customer Experience | Pixis",{"canonical":9,"robots":2440},[],[],{"facebook":2443,"twitter":2444},{"description":382,"title":2438},{"description":382,"title":2438},[2446],{"title":526,"slug":527},[2448],{"blocks":2449},[2450],{"type":437,"textBlock":2451},"\u003Cspan style=\"font-weight:400;\">Customer experience (CX) encompasses all interactions a customer has with a brand throughout their relationship. It includes factors such as product quality, customer service, website usability, and marketing communications. Positive customer experience builds trust, loyalty, and long-term business success.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Every touchpoint a customer encounters—whether browsing a website, contacting support, or making a purchase—shapes their perception of a brand. Companies with strong customer experience strategies ensure that these interactions are seamless, consistent, and satisfying. For example, an airline that offers easy booking, helpful notifications, and responsive support is more likely to earn repeat business.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Customer experience extends beyond individual transactions. It includes the emotional impact of how customers feel when interacting with a brand, which influences their willingness to continue doing business.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Businesses gather feedback through surveys, reviews, and social listening to assess customer satisfaction. They also track key performance indicators (KPIs), such as net promoter score (NPS), customer satisfaction score (CSAT), and customer retention rates.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">CX strategies prioritize removing pain points and delivering proactive support. Personalization, fast response times, and user-friendly digital interfaces are key elements of strong customer experience.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Excellent customer experience drives customer loyalty and word-of-mouth marketing. Satisfied customers are more likely to become repeat buyers and brand advocates. Improved CX also reduces churn, as customers are less likely to leave when their needs are consistently met.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">E-commerce platforms optimize product discovery and checkout experiences to improve CX. Service-based businesses focus on fast response times and effective support.\u003C/span>",{"uri":2453,"id":2454,"title":2455,"url":2456,"postDate":753,"dateUpdated":2457,"slug":2458,"sectionHandle":373,"type":410,"authors":2459,"seo":2467,"categories":2475,"contentArea":2477,"siteName":371},"glossary/customer-journey","17545","Customer Journey","https://pixis-brand-web-1dfin.sevalla.page/glossary/customer-journey/","2025-04-17T03:17:22-04:00","customer-journey",[2460],{"fullName":371,"asset":2461,"position":419,"bio":9,"linkedIn":9,"authorPage":2466},[2462],{"type":27,"image":2463,"mobileImage":2465},[2464],{"src":417,"alt":9},[],[],{"title":2468,"description":382,"advanced":2469,"keywords":2471,"social":2472},"Customer Journey | Pixis",{"canonical":9,"robots":2470},[],[],{"facebook":2473,"twitter":2474},{"description":382,"title":2468},{"description":382,"title":2468},[2476],{"title":526,"slug":527},[2478],{"blocks":2479},[2480],{"type":437,"textBlock":2481},"The customer journey refers to the entire process customers go through when interacting with a brand, from initial awareness to post-purchase engagement. This journey typically includes stages such as awareness, consideration, decision-making, and loyalty.\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Customers rarely make purchases on their first interaction with a brand. They often research options, compare competitors, and evaluate reviews before committing to a product or service. Businesses that understand the journey can provide relevant information and support at each stage, guiding customers toward conversion.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">For example, during the awareness stage, content marketing and social media ads introduce a brand. In the consideration stage, detailed product pages and testimonials help build trust. Personalized offers and support can then encourage purchase decisions.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Mapping the customer journey allows businesses to optimize each touchpoint for maximum impact.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Customer journey mapping involves tracking user interactions and categorizing them into key stages. Data from website analytics, CRM systems, and customer feedback helps identify common paths customers take.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Businesses use this data to create content and campaigns that align with each stage. For example, educational blog posts target users in the early stages, while product demos appeal to users nearing a decision.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Customer journey mapping improves engagement and conversion rates by ensuring that customers receive the right support at the right time. It also helps businesses identify weak points, such as pages with high drop-off rates, enabling them to optimize the experience.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">A well-managed customer journey builds trust and loyalty, which increases customer lifetime value (CLV).\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Retailers design omnichannel journeys that integrate online and in-store experiences.\u003C/span>",{"uri":2483,"id":2484,"title":2485,"url":2486,"postDate":753,"dateUpdated":2457,"slug":2487,"sectionHandle":373,"type":410,"authors":2488,"seo":2496,"categories":2504,"contentArea":2506,"siteName":371},"glossary/customer-lifecycle","17551","Customer Lifecycle","https://pixis-brand-web-1dfin.sevalla.page/glossary/customer-lifecycle/","customer-lifecycle",[2489],{"fullName":371,"asset":2490,"position":419,"bio":9,"linkedIn":9,"authorPage":2495},[2491],{"type":27,"image":2492,"mobileImage":2494},[2493],{"src":417,"alt":9},[],[],{"title":2497,"description":382,"advanced":2498,"keywords":2500,"social":2501},"Customer Lifecycle | Pixis",{"canonical":9,"robots":2499},[],[],{"facebook":2502,"twitter":2503},{"description":382,"title":2497},{"description":382,"title":2497},[2505],{"title":526,"slug":527},[2507],{"blocks":2508},[2509],{"type":437,"textBlock":2510},"\u003Cspan style=\"font-weight:400;\">The customer lifecycle represents the stages a customer goes through during their relationship with a business. These stages typically include acquisition, activation, retention, and advocacy. Managing the customer lifecycle involves nurturing relationships to maximize long-term value.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Customers start their journey by becoming aware of a business and deciding to make a purchase. Once they are onboarded or activated, businesses focus on retaining them through ongoing engagement and support. Over time, satisfied customers may become advocates who refer others or provide testimonials.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Each stage of the lifecycle presents opportunities to deepen the relationship. Businesses that understand the lifecycle can implement strategies to strengthen loyalty and drive repeat purchases.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Lifecycle management relies on data collection and customer segmentation. Businesses track metrics such as acquisition costs, customer retention rates, and advocacy behaviors. Strategies are developed for each stage. For example, onboarding programs help new customers quickly realize the value of a product, while loyalty programs reward long-term engagement.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Businesses also monitor customer feedback to ensure that needs are met throughout the lifecycle.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Effective lifecycle management increases customer retention and lifetime value. Engaged customers are more likely to stay loyal and refer others. Businesses that optimize each lifecycle stage reduce churn and improve profitability.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Subscription-based businesses use lifecycle management to reduce churn by improving engagement during critical points, such as renewal periods. E-commerce brands implement personalized campaigns to encourage repeat purchases.\u003C/span>",{"uri":2512,"id":2513,"title":2514,"url":2515,"postDate":753,"dateUpdated":754,"slug":2516,"sectionHandle":373,"type":410,"authors":2517,"seo":2525,"categories":2533,"contentArea":2535,"siteName":371},"glossary/customer-lifecycle-management-clm","17557","Customer Lifecycle Management (CLM)","https://pixis-brand-web-1dfin.sevalla.page/glossary/customer-lifecycle-management-clm/","customer-lifecycle-management-clm",[2518],{"fullName":371,"asset":2519,"position":419,"bio":9,"linkedIn":9,"authorPage":2524},[2520],{"type":27,"image":2521,"mobileImage":2523},[2522],{"src":417,"alt":9},[],[],{"title":2526,"description":382,"advanced":2527,"keywords":2529,"social":2530},"Customer Lifecycle Management (CLM) | Pixis",{"canonical":9,"robots":2528},[],[],{"facebook":2531,"twitter":2532},{"description":382,"title":2526},{"description":382,"title":2526},[2534],{"title":526,"slug":527},[2536],{"blocks":2537},[2538],{"type":437,"textBlock":2539},"\u003Cspan style=\"font-weight:400;\">Customer Lifecycle Management (CLM) involves overseeing and optimizing the various stages of a customer’s relationship with a business. The goal is to increase customer lifetime value by delivering targeted strategies at each stage, from acquisition to retention and advocacy.\u003C/span>\n\n\u003Cb>What You Need to Know\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">CLM focuses on providing a seamless and positive experience throughout the customer journey. It emphasizes understanding the unique needs and expectations of customers at each stage of the lifecycle. For example, new customers may require onboarding and education, while long-term customers benefit from loyalty incentives and personalized offers.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">By aligning strategies with lifecycle stages, businesses improve engagement, reduce churn, and foster stronger relationships.\u003C/span>\n\n\u003Cb>How It Works\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Businesses implement tools like CRM platforms to track and manage customer interactions. Data analytics help identify key behaviors that indicate progression through lifecycle stages. Marketers create targeted campaigns that address specific goals, such as increasing activation rates or reducing churn.\u003C/span>\n\n\u003Cspan style=\"font-weight:400;\">Regular performance reviews allow businesses to adjust strategies based on customer feedback and engagement metrics.\u003C/span>\n\n\u003Cb>Advantages\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">CLM maximizes customer lifetime value by ensuring that customers remain engaged and satisfied. Effective management reduces the risk of churn and boosts profitability. Businesses also benefit from improved efficiency, as resources are focused on high-impact lifecycle stages.\u003C/span>\n\n\u003Cb>Applications and Use Cases\u003C/b>\n\n\u003Cspan style=\"font-weight:400;\">Retailers use CLM to personalize marketing campaigns based on customer purchase history.\u003C/span>",{"uri":2541,"id":2542,"title":2543,"url":2544,"postDate":2545,"dateUpdated":2546,"slug":2547,"sectionHandle":373,"type":410,"authors":2548,"seo":2556,"categories":2564,"contentArea":2566,"siteName":371},"glossary/data-agnostic","17797","Data Agnostic","https://pixis-brand-web-1dfin.sevalla.page/glossary/data-agnostic/","2025-03-06T07:15:53-05:00","2025-04-17T03:17:43-04:00","data-agnostic",[2549],{"fullName":371,"asset":2550,"position":419,"bio":9,"linkedIn":9,"authorPage":2555},[2551],{"type":27,"image":2552,"mobileImage":2554},[2553],{"src":417,"alt":9},[],[],{"title":2557,"description":382,"advanced":2558,"keywords":2560,"social":2561},"Data Agnostic | Pixis",{"canonical":9,"robots":2559},[],[],{"facebook":2562,"twitter":2563},{"description":382,"title":2557},{"description":382,"title":2557},[2565],{"title":1308,"slug":1309},[2567],{"blocks":2568},[2569],{"type":437,"textBlock":2570},"Data Agnostic refers to the ability of an Artificial Intelligence (AI) system to operate without being specifically tailored or trained on a particular type or set of data. This is useful in situations where an AI system needs to be applied to a diverse range of data sources or types, or where the data available for training is limited or unreliable. For example, the Pixis AI systems are data agnostic and can learn from any and all types of data that are provided to them.",{"uri":2572,"id":2573,"title":2574,"url":2575,"postDate":2576,"dateUpdated":2577,"slug":2578,"sectionHandle":373,"type":410,"authors":2579,"seo":2587,"categories":2595,"contentArea":2597,"siteName":371},"glossary/data-augmentation","17839","Data Augmentation","https://pixis-brand-web-1dfin.sevalla.page/glossary/data-augmentation/","2025-03-06T07:19:33-05:00","2025-04-17T03:17:46-04:00","data-augmentation",[2580],{"fullName":371,"asset":2581,"position":419,"bio":9,"linkedIn":9,"authorPage":2586},[2582],{"type":27,"image":2583,"mobileImage":2585},[2584],{"src":417,"alt":9},[],[],{"title":2588,"description":382,"advanced":2589,"keywords":2591,"social":2592},"Data Augmentation | Pixis",{"canonical":9,"robots":2590},[],[],{"facebook":2593,"twitter":2594},{"description":382,"title":2588},{"description":382,"title":2588},[2596],{"title":1308,"slug":1309},[2598],{"blocks":2599},[2600],{"type":437,"textBlock":2601},"In the context of Artificial Intelligence (AI), Data Augmentation refers to the process of generating additional data samples from existing ones. It is a common technique used in machine learning to increase the size and diversity of the training dataset, in order to improve the performance of the models, especially when the original dataset is small or lacks diversity. Pixis uses data augmentation to train its codeless AI infrastructure and to refine the performance of its AI models to produce better results for the users.",{"uri":2603,"id":2604,"title":2605,"url":2606,"postDate":2607,"dateUpdated":2608,"slug":2609,"sectionHandle":373,"type":410,"authors":2610,"seo":2618,"categories":2626,"contentArea":2628,"siteName":371},"glossary/decision-intelligence","17851","Decision Intelligence","https://pixis-brand-web-1dfin.sevalla.page/glossary/decision-intelligence/","2025-03-06T07:20:17-05:00","2025-04-17T03:17:47-04:00","decision-intelligence",[2611],{"fullName":371,"asset":2612,"position":419,"bio":9,"linkedIn":9,"authorPage":2617},[2613],{"type":27,"image":2614,"mobileImage":2616},[2615],{"src":417,"alt":9},[],[],{"title":2619,"description":382,"advanced":2620,"keywords":2622,"social":2623},"Decision Intelligence | Pixis",{"canonical":9,"robots":2621},[],[],{"facebook":2624,"twitter":2625},{"description":382,"title":2619},{"description":382,"title":2619},[2627],{"title":1308,"slug":1309},[2629],{"blocks":2630},[2631],{"type":437,"textBlock":2632},"Decision Intelligence is a field of Artificial Intelligence (AI) that focuses on using data and algorithms to make informed decisions. This can involve analyzing large amounts of data, using machine learning techniques to identify patterns and trends, and using these insights to make predictions or recommendations.\n\nPixis enables Decision Intelligence in marketing and demand generation to help organizations make more informed and data-driven decisions, which can lead to improved efficiency and effectiveness.",{"uri":2634,"id":2635,"title":2636,"url":2637,"postDate":2638,"dateUpdated":2608,"slug":2639,"sectionHandle":373,"type":410,"authors":2640,"seo":2648,"categories":2656,"contentArea":2658,"siteName":371},"glossary/decision-tree","17845","Decision Tree","https://pixis-brand-web-1dfin.sevalla.page/glossary/decision-tree/","2025-03-06T07:19:56-05:00","decision-tree",[2641],{"fullName":371,"asset":2642,"position":419,"bio":9,"linkedIn":9,"authorPage":2647},[2643],{"type":27,"image":2644,"mobileImage":2646},[2645],{"src":417,"alt":9},[],[],{"title":2649,"description":382,"advanced":2650,"keywords":2652,"social":2653},"Decision Tree | Pixis",{"canonical":9,"robots":2651},[],[],{"facebook":2654,"twitter":2655},{"description":382,"title":2649},{"description":382,"title":2649},[2657],{"title":1308,"slug":1309},[2659],{"blocks":2660},[2661],{"type":437,"textBlock":2662},"A Decision Tree is a type of machine learning algorithm that is used to make predictions or decisions based on a set of rules. It is called a \"decision tree\" because it is structured like a tree, with a series of branches representing different decisions or outcomes. At each branching point in the tree, the algorithm considers a different feature or attribute of the data and uses this information to decide which branch to follow.",{"uri":2664,"id":2665,"title":2666,"url":2667,"postDate":2668,"dateUpdated":2669,"slug":2670,"sectionHandle":373,"type":410,"authors":2671,"seo":2679,"categories":2687,"contentArea":2689,"siteName":371},"glossary/deep-learning","17827","Deep Learning","https://pixis-brand-web-1dfin.sevalla.page/glossary/deep-learning/","2025-03-06T07:18:23-05:00","2025-04-17T03:17:45-04:00","deep-learning",[2672],{"fullName":371,"asset":2673,"position":419,"bio":9,"linkedIn":9,"authorPage":2678},[2674],{"type":27,"image":2675,"mobileImage":2677},[2676],{"src":417,"alt":9},[],[],{"title":2680,"description":382,"advanced":2681,"keywords":2683,"social":2684},"Deep Learning | Pixis",{"canonical":9,"robots":2682},[],[],{"facebook":2685,"twitter":2686},{"description":382,"title":2680},{"description":382,"title":2680},[2688],{"title":1308,"slug":1309},[2690],{"blocks":2691},[2692],{"type":437,"textBlock":2693},"Deep Learning is a subfield of machine learning that involves the use of artificial neural networks, which are complex mathematical models inspired by the structure and function of the human brain. Deep Learning algorithms are designed to learn from large amounts of data by identifying patterns and features in the data and using these patterns to make predictions or decisions. They are particularly effective at tasks such as image and speech recognition, natural language processing, and decision-making, and are used in a wide variety of applications, including self-driving cars, language translation, and personal assistants.",{"uri":2695,"id":2696,"title":2697,"url":2698,"postDate":2699,"dateUpdated":2669,"slug":2700,"sectionHandle":373,"type":410,"authors":2701,"seo":2709,"categories":2717,"contentArea":2719,"siteName":371},"glossary/descriptive-analytics","17821","Descriptive Analytics","https://pixis-brand-web-1dfin.sevalla.page/glossary/descriptive-analytics/","2025-03-06T07:17:57-05:00","descriptive-analytics",[2702],{"fullName":371,"asset":2703,"position":419,"bio":9,"linkedIn":9,"authorPage":2708},[2704],{"type":27,"image":2705,"mobileImage":2707},[2706],{"src":417,"alt":9},[],[],{"title":2710,"description":382,"advanced":2711,"keywords":2713,"social":2714},"Descriptive Analytics | Pixis",{"canonical":9,"robots":2712},[],[],{"facebook":2715,"twitter":2716},{"description":382,"title":2710},{"description":382,"title":2710},[2718],{"title":1308,"slug":1309},[2720],{"blocks":2721},[2722],{"type":437,"textBlock":2723},"In the context of Artificial Intelligence (AI), Descriptive Analytics involves using AI algorithms and models for understanding patterns and trends in data to inform decision-making and guide business strategy. Please note that descriptive analytics does not necessarily provide insights into what will happen in the future or how to take action based on the data. For that, other types of data analysis, such as predictive analytics or prescriptive analytics, may be more appropriate.",{"uri":2725,"id":2726,"title":2727,"url":2728,"postDate":2729,"dateUpdated":2577,"slug":2730,"sectionHandle":373,"type":410,"authors":2731,"seo":2739,"categories":2747,"contentArea":2749,"siteName":371},"glossary/deterministic-dependency-parsing","17833","Deterministic Dependency Parsing","https://pixis-brand-web-1dfin.sevalla.page/glossary/deterministic-dependency-parsing/","2025-03-06T07:18:49-05:00","deterministic-dependency-parsing",[2732],{"fullName":371,"asset":2733,"position":419,"bio":9,"linkedIn":9,"authorPage":2738},[2734],{"type":27,"image":2735,"mobileImage":2737},[2736],{"src":417,"alt":9},[],[],{"title":2740,"description":382,"advanced":2741,"keywords":2743,"social":2744},"Deterministic Dependency Parsing | Pixis",{"canonical":9,"robots":2742},[],[],{"facebook":2745,"twitter":2746},{"description":382,"title":2740},{"description":382,"title":2740},[2748],{"title":1308,"slug":1309},[2750],{"blocks":2751},[2752],{"type":437,"textBlock":2753},"Deterministic Dependency Parsing is a process used by Artificial Intelligence (AI) systems to analyze and understand the relationships between words in a sentence. Essentially, it helps the AI to understand the meaning of a sentence and accurately interpret the intended message. For example, \"the cat sat on the mat.\" In this sentence, Deterministic Dependency Parsing would help the AI understand these relationships and recognize that \"cat\" is the noun that is performing the action of \"sitting,\" and \"mat\" is the noun that is being acted upon.",{"uri":2755,"id":2756,"title":2757,"url":2758,"postDate":2759,"dateUpdated":2760,"slug":2761,"sectionHandle":373,"type":410,"authors":2762,"seo":2770,"categories":2778,"contentArea":2780,"siteName":371},"glossary/diagnostic-analytics","17809","Diagnostic Analytics","https://pixis-brand-web-1dfin.sevalla.page/glossary/diagnostic-analytics/","2025-03-06T07:17:01-05:00","2025-04-17T03:17:44-04:00","diagnostic-analytics",[2763],{"fullName":371,"asset":2764,"position":419,"bio":9,"linkedIn":9,"authorPage":2769},[2765],{"type":27,"image":2766,"mobileImage":2768},[2767],{"src":417,"alt":9},[],[],{"title":2771,"description":382,"advanced":2772,"keywords":2774,"social":2775},"Diagnostic Analytics | Pixis",{"canonical":9,"robots":2773},[],[],{"facebook":2776,"twitter":2777},{"description":382,"title":2771},{"description":382,"title":2771},[2779],{"title":1308,"slug":1309},[2781],{"blocks":2782},[2783],{"type":437,"textBlock":2784},"In the context of Artificial Intelligence (AI), Diagnostic Analytics involves the use of machine learning algorithms and other AI techniques to analyze data and identify patterns that can help diagnose and solve problems. This can involve analyzing large amounts of data from multiple sources to identify patterns or trends that might not be immediately visible to humans.",{"uri":2786,"id":2787,"title":2788,"url":2789,"postDate":2790,"dateUpdated":2546,"slug":2791,"sectionHandle":373,"type":410,"authors":2792,"seo":2800,"categories":2808,"contentArea":2810,"siteName":371},"glossary/domain-agnostic-ai","17803","Domain Agnostic AI","https://pixis-brand-web-1dfin.sevalla.page/glossary/domain-agnostic-ai/","2025-03-06T07:16:34-05:00","domain-agnostic-ai",[2793],{"fullName":371,"asset":2794,"position":419,"bio":9,"linkedIn":9,"authorPage":2799},[2795],{"type":27,"image":2796,"mobileImage":2798},[2797],{"src":417,"alt":9},[],[],{"title":2801,"description":382,"advanced":2802,"keywords":2804,"social":2805},"Domain Agnostic AI | Pixis",{"canonical":9,"robots":2803},[],[],{"facebook":2806,"twitter":2807},{"description":382,"title":2801},{"description":382,"title":2801},[2809],{"title":1308,"slug":1309},[2811],{"blocks":2812},[2813],{"type":437,"textBlock":2814},"Domain Agnostic AI refers to an AI model or system that is designed to be flexible and adaptable to all business domains. It can be trained and used on a wide range of tasks and data types. It is useful in situations where there is a limited prior understanding of the type of data or tasks to which the model will be applied. They offer a more flexible approach to AI, as opposed to domain-specific models, which are limited to specific tasks or types of data.",{"uri":2816,"id":2817,"title":2818,"url":2819,"postDate":2820,"dateUpdated":2760,"slug":2821,"sectionHandle":373,"type":410,"authors":2822,"seo":2830,"categories":2838,"contentArea":2840,"siteName":371},"glossary/dynamic-dashboard","17815","Dynamic Dashboard","https://pixis-brand-web-1dfin.sevalla.page/glossary/dynamic-dashboard/","2025-03-06T07:17:32-05:00","dynamic-dashboard",[2823],{"fullName":371,"asset":2824,"position":419,"bio":9,"linkedIn":9,"authorPage":2829},[2825],{"type":27,"image":2826,"mobileImage":2828},[2827],{"src":417,"alt":9},[],[],{"title":2831,"description":382,"advanced":2832,"keywords":2834,"social":2835},"Dynamic Dashboard | Pixis",{"canonical":9,"robots":2833},[],[],{"facebook":2836,"twitter":2837},{"description":382,"title":2831},{"description":382,"title":2831},[2839],{"title":1308,"slug":1309},[2841],{"blocks":2842},[2843],{"type":437,"textBlock":2844},"A Dynamic Dashboard is a type of interactive data visualization tool that allows users to explore and analyze data in real-time. It typically consists of a series of graphs, charts, and other visual elements that display data in an easy-to-understand format. In the context of Artificial Intelligence (AI), dynamic dashboards are particularly useful as they can be configured to automatically update as new data becomes available. This makes it easier for users to stay up-to-date with the latest insights and trends, and to make data-driven decisions in real time.\n\nPixis uses Dynamic Dashboards to display data and insights generated by its AIs in a visually appealing and easily understandable manner, allowing business users to quickly understand and act on the insights provided by its AI systems.",{"uri":2846,"id":2847,"title":2848,"url":2849,"postDate":2850,"dateUpdated":2851,"slug":2852,"sectionHandle":373,"type":410,"authors":2853,"seo":2861,"categories":2869,"contentArea":2871,"siteName":371},"glossary/enterprise-internet-of-things-iot","17857","Enterprise Internet of Things (IoT)","https://pixis-brand-web-1dfin.sevalla.page/glossary/enterprise-internet-of-things-iot/","2025-03-06T07:20:46-05:00","2025-04-17T03:17:48-04:00","enterprise-internet-of-things-iot",[2854],{"fullName":371,"asset":2855,"position":419,"bio":9,"linkedIn":9,"authorPage":2860},[2856],{"type":27,"image":2857,"mobileImage":2859},[2858],{"src":417,"alt":9},[],[],{"title":2862,"description":382,"advanced":2863,"keywords":2865,"social":2866},"Enterprise Internet of Things (IoT) | Pixis",{"canonical":9,"robots":2864},[],[],{"facebook":2867,"twitter":2868},{"description":382,"title":2862},{"description":382,"title":2862},[2870],{"title":1308,"slug":1309},[2872],{"blocks":2873},[2874],{"type":437,"textBlock":2875},"Enterprise Internet of Things (IoT) refers to the use of connected devices, sensors, and systems within a business or organization to collect, transmit, and analyze data. AI can be used to analyze this data to identify patterns and trends and make recommendations or decisions based on this analysis, to improve operational efficiency, and optimize business processes.",{"uri":2877,"id":2878,"title":2879,"url":2880,"postDate":2881,"dateUpdated":2851,"slug":2882,"sectionHandle":373,"type":410,"authors":2883,"seo":2891,"categories":2899,"contentArea":2901,"siteName":371},"glossary/generative-adversarial-networks","17863","Generative Adversarial Networks","https://pixis-brand-web-1dfin.sevalla.page/glossary/generative-adversarial-networks/","2025-03-06T07:21:10-05:00","generative-adversarial-networks",[2884],{"fullName":371,"asset":2885,"position":419,"bio":9,"linkedIn":9,"authorPage":2890},[2886],{"type":27,"image":2887,"mobileImage":2889},[2888],{"src":417,"alt":9},[],[],{"title":2892,"description":382,"advanced":2893,"keywords":2895,"social":2896},"Generative Adversarial Networks | Pixis",{"canonical":9,"robots":2894},[],[],{"facebook":2897,"twitter":2898},{"description":382,"title":2892},{"description":382,"title":2892},[2900],{"title":1308,"slug":1309},[2902],{"blocks":2903},[2904],{"type":437,"textBlock":2905},"\u003Cspan style=\"font-weight:400;\">A class of machine learning models that consist of two neural networks: a generator and a discriminator. GANs are used for generating new data that resembles a given training dataset. The generator attempts to create synthetic data samples, such as images, audio, or text, that resemble the real data from the training set. The discriminator network, on the other hand, aims to distinguish between real data samples from the training set and the synthetic data samples created by the generator.\u003C/span>",{"uri":2907,"id":2908,"title":2909,"url":2910,"postDate":2911,"dateUpdated":2851,"slug":2912,"sectionHandle":373,"type":410,"authors":2913,"seo":2921,"categories":2929,"contentArea":2931,"siteName":371},"glossary/gpt-3","17869","GPT-3","https://pixis-brand-web-1dfin.sevalla.page/glossary/gpt-3/","2025-03-06T07:21:35-05:00","gpt-3",[2914],{"fullName":371,"asset":2915,"position":419,"bio":9,"linkedIn":9,"authorPage":2920},[2916],{"type":27,"image":2917,"mobileImage":2919},[2918],{"src":417,"alt":9},[],[],{"title":2922,"description":382,"advanced":2923,"keywords":2925,"social":2926},"GPT-3 | Pixis",{"canonical":9,"robots":2924},[],[],{"facebook":2927,"twitter":2928},{"description":382,"title":2922},{"description":382,"title":2922},[2930],{"title":1308,"slug":1309},[2932],{"blocks":2933},[2934],{"type":437,"textBlock":2935},"GPT-3 (Generative Pre-training Transformer 3) is a state-of-the-art Artificial Intelligence (AI) language model designed to process and generate human-like language. GPT-3 is trained on a massive amount of data, which allows it to have a deep understanding of language and the ability to generate responses that are relevant and appropriate in a given context. It is also able to learn and adapt over time, allowing it to improve its performance on various language-based tasks.\n\nOne of the key features of GPT-3 is its ability to generate text that is coherent and flows naturally, making it well-suited for tasks such as translation, text generation, and text summarization. Pixis AI uses GPT-3 to help marketers generate contextual communication for their marketing campaigns across platforms with speed, and at scale.",{"uri":2937,"id":2938,"title":2939,"url":2940,"postDate":2941,"dateUpdated":2942,"slug":2943,"sectionHandle":373,"type":410,"authors":2944,"seo":2952,"categories":2960,"contentArea":2962,"siteName":371},"glossary/hyperparameters","17875","Hyperparameters","https://pixis-brand-web-1dfin.sevalla.page/glossary/hyperparameters/","2025-03-06T07:21:58-05:00","2025-04-17T03:17:49-04:00","hyperparameters",[2945],{"fullName":371,"asset":2946,"position":419,"bio":9,"linkedIn":9,"authorPage":2951},[2947],{"type":27,"image":2948,"mobileImage":2950},[2949],{"src":417,"alt":9},[],[],{"title":2953,"description":382,"advanced":2954,"keywords":2956,"social":2957},"Hyperparameters | Pixis",{"canonical":9,"robots":2955},[],[],{"facebook":2958,"twitter":2959},{"description":382,"title":2953},{"description":382,"title":2953},[2961],{"title":1308,"slug":1309},[2963],{"blocks":2964},[2965],{"type":437,"textBlock":2966},"Hyperparameters are settings or parameters that are chosen before training a machine learning model to adjust or control its learning process and improve its performance and accuracy. Some examples of Hyperparameters include the number of layers in a neural network, the number of neurons in each layer, the learning rate, etc. The Hyperparameters are usually determined through a process called hyperparameter tuning, where different combinations of hyperparameters are tested to find the optimal combination that results in the best model performance.\n\nFor example, we may have a Hyperparameter called the \"learning rate\" which determines how fast the algorithm learns from the data. If the learning rate is too high, the algorithm may overshoot the optimal solution and not perform well on the test data. On the other hand, if the learning rate is too low, the algorithm may take too long to learn and also not perform well.",{"uri":2968,"id":2969,"title":2970,"url":2971,"postDate":2972,"dateUpdated":2942,"slug":2973,"sectionHandle":373,"type":410,"authors":2974,"seo":2982,"categories":2990,"contentArea":2992,"siteName":371},"glossary/inference","17881","Inference","https://pixis-brand-web-1dfin.sevalla.page/glossary/inference/","2025-03-06T07:22:21-05:00","inference",[2975],{"fullName":371,"asset":2976,"position":419,"bio":9,"linkedIn":9,"authorPage":2981},[2977],{"type":27,"image":2978,"mobileImage":2980},[2979],{"src":417,"alt":9},[],[],{"title":2983,"description":382,"advanced":2984,"keywords":2986,"social":2987},"Inference | Pixis",{"canonical":9,"robots":2985},[],[],{"facebook":2988,"twitter":2989},{"description":382,"title":2983},{"description":382,"title":2983},[2991],{"title":1308,"slug":1309},[2993],{"blocks":2994},[2995],{"type":437,"textBlock":2996},"Inference in the context of AI refers to the process of using previously learned knowledge to make predictions or conclusions about new situations or data. This can be useful in a variety of applications, such as helping robots navigate unfamiliar environments or allowing AI assistants to understand and respond to natural language input from users.\n\nFor example, if an AI system has learned about different types of animals, it can infer that a creature with a long neck and four legs is likely a giraffe, even if it has never seen a giraffe before. Essentially, it is using what it has learned to make an educated guess about something it has not encountered before. In this way, AI systems can make intelligent decisions and predictions based on what they have learned from previous experiences.",{"uri":2998,"id":2999,"title":3000,"url":3001,"postDate":3002,"dateUpdated":3003,"slug":3004,"sectionHandle":373,"type":410,"authors":3005,"seo":3013,"categories":3021,"contentArea":3023,"siteName":371},"glossary/latent-space","17887","Latent Space","https://pixis-brand-web-1dfin.sevalla.page/glossary/latent-space/","2025-03-06T07:22:44-05:00","2025-04-17T03:17:50-04:00","latent-space",[3006],{"fullName":371,"asset":3007,"position":419,"bio":9,"linkedIn":9,"authorPage":3012},[3008],{"type":27,"image":3009,"mobileImage":3011},[3010],{"src":417,"alt":9},[],[],{"title":3014,"description":382,"advanced":3015,"keywords":3017,"social":3018},"Latent Space | Pixis",{"canonical":9,"robots":3016},[],[],{"facebook":3019,"twitter":3020},{"description":382,"title":3014},{"description":382,"title":3014},[3022],{"title":1308,"slug":1309},[3024],{"blocks":3025},[3026],{"type":437,"textBlock":3027},"\u003Cspan style=\"font-weight:400;\">Latent space refers to a mathematical representation or space where complex data or information is encoded into a more condensed and meaningful form. It is often used in machine learning and artificial intelligence to capture the essence or underlying structure of data, allowing for exploration, manipulation, and generation of new data points with similar characteristics.\u003C/span>",{"uri":3029,"id":3030,"title":3031,"url":3032,"postDate":3033,"dateUpdated":3003,"slug":3034,"sectionHandle":373,"type":410,"authors":3035,"seo":3043,"categories":3051,"contentArea":3053,"siteName":371},"glossary/lstm","17893","LSTM","https://pixis-brand-web-1dfin.sevalla.page/glossary/lstm/","2025-03-06T07:23:09-05:00","lstm",[3036],{"fullName":371,"asset":3037,"position":419,"bio":9,"linkedIn":9,"authorPage":3042},[3038],{"type":27,"image":3039,"mobileImage":3041},[3040],{"src":417,"alt":9},[],[],{"title":3044,"description":382,"advanced":3045,"keywords":3047,"social":3048},"LSTM | Pixis",{"canonical":9,"robots":3046},[],[],{"facebook":3049,"twitter":3050},{"description":382,"title":3044},{"description":382,"title":3044},[3052],{"title":1308,"slug":1309},[3054],{"blocks":3055},[3056],{"type":437,"textBlock":3057},"LSTM stands for Long Short-Term Memory. It is a type of artificial neural network used in the field of Artificial Intelligence (AI) for analyzing and making predictions based on large amounts of data, and they are often used in a variety of AI applications, including natural language processing, speech recognition, and machine translation. For example, an LSTM might be used to analyze a large dataset of customer reviews and make predictions about which products will be most popular in the future.\n\nOne of the key features of LSTMs is their ability to remember important information over a long period of time. This is important because it allows the AI to make better predictions based on patterns that it has observed over a longer period of time.",{"uri":3059,"id":3060,"title":3061,"url":3062,"postDate":3063,"dateUpdated":3064,"slug":3065,"sectionHandle":373,"type":410,"authors":3066,"seo":3074,"categories":3082,"contentArea":3084,"siteName":371},"glossary/metaheuristic","17899","Metaheuristic","https://pixis-brand-web-1dfin.sevalla.page/glossary/metaheuristic/","2025-03-06T07:23:32-05:00","2025-04-17T03:17:51-04:00","metaheuristic",[3067],{"fullName":371,"asset":3068,"position":419,"bio":9,"linkedIn":9,"authorPage":3073},[3069],{"type":27,"image":3070,"mobileImage":3072},[3071],{"src":417,"alt":9},[],[],{"title":3075,"description":382,"advanced":3076,"keywords":3078,"social":3079},"Metaheuristic | Pixis",{"canonical":9,"robots":3077},[],[],{"facebook":3080,"twitter":3081},{"description":382,"title":3075},{"description":382,"title":3075},[3083],{"title":1308,"slug":1309},[3085],{"blocks":3086},[3087],{"type":437,"textBlock":3088},"Metaheuristics are a type of Artificial Intelligence (AI) algorithm that can be used to solve complex optimization problems by finding good solutions that are not necessarily optimal. They work by using a set of heuristics, or rules of thumb, to guide the search for solutions in a flexible and adaptive way. Metaheuristics are often used when traditional optimization techniques are too slow or too expensive, or when the problem is too large to solve using exact methods. They can be applied to a wide range of problems, including optimization, scheduling, routing, and resource allocation.\n\nPixis AI uses metaheuristic models to find the best-optimized solutions for problem statements and challenges in marketing.",{"uri":3090,"id":3091,"title":3092,"url":3093,"postDate":3094,"dateUpdated":3064,"slug":3095,"sectionHandle":373,"type":410,"authors":3096,"seo":3104,"categories":3112,"contentArea":3114,"siteName":371},"glossary/natural-language-generation","17905","Natural Language Generation","https://pixis-brand-web-1dfin.sevalla.page/glossary/natural-language-generation/","2025-03-06T07:23:51-05:00","natural-language-generation",[3097],{"fullName":371,"asset":3098,"position":419,"bio":9,"linkedIn":9,"authorPage":3103},[3099],{"type":27,"image":3100,"mobileImage":3102},[3101],{"src":417,"alt":9},[],[],{"title":3105,"description":382,"advanced":3106,"keywords":3108,"social":3109},"Natural Language Generation | Pixis",{"canonical":9,"robots":3107},[],[],{"facebook":3110,"twitter":3111},{"description":382,"title":3105},{"description":382,"title":3105},[3113],{"title":1308,"slug":1309},[3115],{"blocks":3116},[3117],{"type":437,"textBlock":3118},"Natural Language Generation (NLG) is a field of Artificial Intelligence (AI) that involves creating a human-like language from data or computer-generated information. It allows computers to generate texts or spoken language that can be understood by humans, enabling a more natural and intuitive way of communication. Pixis enables companies to use NLG to create highly relevant and creative content that can effectively engage and convert their target audience.",{"uri":3120,"id":3121,"title":3122,"url":3123,"postDate":3124,"dateUpdated":3125,"slug":3126,"sectionHandle":373,"type":410,"authors":3127,"seo":3135,"categories":3143,"contentArea":3145,"siteName":371},"glossary/natural-language-processing","17911","Natural Language Processing","https://pixis-brand-web-1dfin.sevalla.page/glossary/natural-language-processing/","2025-03-06T07:24:12-05:00","2025-04-17T03:17:52-04:00","natural-language-processing",[3128],{"fullName":371,"asset":3129,"position":419,"bio":9,"linkedIn":9,"authorPage":3134},[3130],{"type":27,"image":3131,"mobileImage":3133},[3132],{"src":417,"alt":9},[],[],{"title":3136,"description":382,"advanced":3137,"keywords":3139,"social":3140},"Natural Language Processing | Pixis",{"canonical":9,"robots":3138},[],[],{"facebook":3141,"twitter":3142},{"description":382,"title":3136},{"description":382,"title":3136},[3144],{"title":1308,"slug":1309},[3146],{"blocks":3147},[3148],{"type":437,"textBlock":3149},"Natural Language Processing (NLP) is a field within Artificial Intelligence (AI) that focuses on the ability of computers to understand, interpret, and generate human language. This can include tasks such as language translation, speech recognition, and text analysis.\n\nIn practical terms, this means that NLP allows computers to process and understand written or spoken language in the same way that a human would. For example, a computer program using NLP could be trained to understand that \"I am hungry\" means the same thing as \"I need food,\" and it could respond appropriately.",{"uri":3151,"id":3152,"title":3153,"url":3154,"postDate":3155,"dateUpdated":3125,"slug":3156,"sectionHandle":373,"type":410,"authors":3157,"seo":3165,"categories":3173,"contentArea":3175,"siteName":371},"glossary/optimization-events","17917","Optimization Events","https://pixis-brand-web-1dfin.sevalla.page/glossary/optimization-events/","2025-03-06T07:24:34-05:00","optimization-events",[3158],{"fullName":371,"asset":3159,"position":419,"bio":9,"linkedIn":9,"authorPage":3164},[3160],{"type":27,"image":3161,"mobileImage":3163},[3162],{"src":417,"alt":9},[],[],{"title":3166,"description":382,"advanced":3167,"keywords":3169,"social":3170},"Optimization Events | Pixis",{"canonical":9,"robots":3168},[],[],{"facebook":3171,"twitter":3172},{"description":382,"title":3166},{"description":382,"title":3166},[3174],{"title":1308,"slug":1309},[3176],{"blocks":3177},[3178],{"type":437,"textBlock":3179},"Optimization Events refer to the process of improving the performance or efficiency of a machine learning model or algorithm. This can be done through various techniques, such as adjusting the model's parameters, selecting different data sets to train the model on, or using different optimization algorithms to find the optimal solution. In the context of Artificial Intelligence (AI), Optimization Events play a critical role in ensuring that machine learning models are able to accurately predict outcomes and make decisions based on the data they are given.",{"uri":3181,"id":3182,"title":3183,"url":3184,"postDate":3185,"dateUpdated":3186,"slug":3187,"sectionHandle":373,"type":410,"authors":3188,"seo":3196,"categories":3204,"contentArea":3206,"siteName":371},"glossary/pico-segmentation","17929","Pico Segmentation","https://pixis-brand-web-1dfin.sevalla.page/glossary/pico-segmentation/","2025-03-06T07:25:24-05:00","2025-04-17T03:17:53-04:00","pico-segmentation",[3189],{"fullName":371,"asset":3190,"position":419,"bio":9,"linkedIn":9,"authorPage":3195},[3191],{"type":27,"image":3192,"mobileImage":3194},[3193],{"src":417,"alt":9},[],[],{"title":3197,"description":382,"advanced":3198,"keywords":3200,"social":3201},"Pico Segmentation | Pixis",{"canonical":9,"robots":3199},[],[],{"facebook":3202,"twitter":3203},{"description":382,"title":3197},{"description":382,"title":3197},[3205],{"title":1308,"slug":1309},[3207],{"blocks":3208},[3209],{"type":437,"textBlock":3210},"Pico segmentation is a way of dividing a large group of people or things into smaller, more specific subgroups. In the context of AI, pico segmentation might be used to identify different characteristics or behaviors within a larger dataset, in order to better understand and predict the actions or preferences of different subgroups within the larger group.\n\nFor example, Pixis AI systems use pico segmentation to identify different trends or patterns within a large group of customers, in order to more effectively target marketing efforts or make recommendations based on their interests.",{"uri":3212,"id":3213,"title":3214,"url":3215,"postDate":3216,"dateUpdated":3186,"slug":3217,"sectionHandle":373,"type":410,"authors":3218,"seo":3226,"categories":3234,"contentArea":3236,"siteName":371},"glossary/predictive-analytics","17923","Predictive Analytics","https://pixis-brand-web-1dfin.sevalla.page/glossary/predictive-analytics/","2025-03-06T07:24:56-05:00","predictive-analytics",[3219],{"fullName":371,"asset":3220,"position":419,"bio":9,"linkedIn":9,"authorPage":3225},[3221],{"type":27,"image":3222,"mobileImage":3224},[3223],{"src":417,"alt":9},[],[],{"title":3227,"description":382,"advanced":3228,"keywords":3230,"social":3231},"Predictive Analytics | Pixis",{"canonical":9,"robots":3229},[],[],{"facebook":3232,"twitter":3233},{"description":382,"title":3227},{"description":382,"title":3227},[3235],{"title":1308,"slug":1309},[3237],{"blocks":3238},[3239],{"type":437,"textBlock":3240},"Predictive Analytics is a type of Artificial Intelligence (AI) that helps to predict future outcomes or events based on past data and patterns. It uses machine learning algorithms to analyze large amounts of data and make predictions about what is likely to happen in the future. This can be used to make better-informed decisions and plan for potential outcomes.",{"uri":3242,"id":3243,"title":3244,"url":3245,"postDate":3246,"dateUpdated":3186,"slug":3247,"sectionHandle":373,"type":410,"authors":3248,"seo":3256,"categories":3264,"contentArea":3266,"siteName":371},"glossary/q-learning","17935","Q-Learning","https://pixis-brand-web-1dfin.sevalla.page/glossary/q-learning/","2025-03-06T07:25:59-05:00","q-learning",[3249],{"fullName":371,"asset":3250,"position":419,"bio":9,"linkedIn":9,"authorPage":3255},[3251],{"type":27,"image":3252,"mobileImage":3254},[3253],{"src":417,"alt":9},[],[],{"title":3257,"description":382,"advanced":3258,"keywords":3260,"social":3261},"Q-Learning | Pixis",{"canonical":9,"robots":3259},[],[],{"facebook":3262,"twitter":3263},{"description":382,"title":3257},{"description":382,"title":3257},[3265],{"title":1308,"slug":1309},[3267],{"blocks":3268},[3269],{"type":437,"textBlock":3270},"Q-Learning is a type of Artificial Intelligence (AI) training that is often used in situations where the computer needs to make decisions based on complex or changing environments. The machine is given a set of possible actions it can take in a given situation, and it is also given a reward or penalty for each action, based on which it then tries different actions and sees which ones result in the best rewards. Over time, the machine learns which actions are most likely to result in positive outcomes and begins to make decisions based on that learning.\n\nQ-Learning is a powerful technique used by the Pixis AI to optimize marketing campaigns by identifying the most effective strategies for reaching target audiences and maximizing ROI.",{"uri":3272,"id":3273,"title":3274,"url":3275,"postDate":3276,"dateUpdated":3277,"slug":3278,"sectionHandle":373,"type":410,"authors":3279,"seo":3287,"categories":3295,"contentArea":3297,"siteName":371},"glossary/reasoning-engine","17971","Reasoning Engine","https://pixis-brand-web-1dfin.sevalla.page/glossary/reasoning-engine/","2025-03-06T07:28:36-05:00","2025-04-17T03:17:56-04:00","reasoning-engine",[3280],{"fullName":371,"asset":3281,"position":419,"bio":9,"linkedIn":9,"authorPage":3286},[3282],{"type":27,"image":3283,"mobileImage":3285},[3284],{"src":417,"alt":9},[],[],{"title":3288,"description":382,"advanced":3289,"keywords":3291,"social":3292},"Reasoning Engine | Pixis",{"canonical":9,"robots":3290},[],[],{"facebook":3293,"twitter":3294},{"description":382,"title":3288},{"description":382,"title":3288},[3296],{"title":1308,"slug":1309},[3298],{"blocks":3299},[3300],{"type":437,"textBlock":3301},"A Reasoning Engine is a component of Artificial Intelligence (AI) that is responsible for making logical deductions and reaching conclusions based on a set of given facts or data. It works by analyzing data, identifying patterns and relationships, and using that information to make decisions or predictions. A Reasoning Engine can be used to analyze a company’s data to help predict future profits or to identify areas where costs can be reduced. This can help organizations make better decisions and improve efficiency by automating tasks and reducing the need for human intervention.",{"uri":3303,"id":3304,"title":3305,"url":3306,"postDate":3307,"dateUpdated":3308,"slug":3309,"sectionHandle":373,"type":410,"authors":3310,"seo":3318,"categories":3326,"contentArea":3328,"siteName":371},"glossary/recommendation","17941","Recommendation","https://pixis-brand-web-1dfin.sevalla.page/glossary/recommendation/","2025-03-06T07:26:30-05:00","2025-04-17T03:17:54-04:00","recommendation",[3311],{"fullName":371,"asset":3312,"position":419,"bio":9,"linkedIn":9,"authorPage":3317},[3313],{"type":27,"image":3314,"mobileImage":3316},[3315],{"src":417,"alt":9},[],[],{"title":3319,"description":382,"advanced":3320,"keywords":3322,"social":3323},"Recommendation | Pixis",{"canonical":9,"robots":3321},[],[],{"facebook":3324,"twitter":3325},{"description":382,"title":3319},{"description":382,"title":3319},[3327],{"title":1308,"slug":1309},[3329],{"blocks":3330},[3331],{"type":437,"textBlock":3332},"Recommendation in the context of Pixis AI refers to the use of Artificial Intelligence (AI) to generate recommendations on an account based on past behavior, interests, and preferences, as well as other factors such as the interests of similar users. Recommendation systems like these can be found in many different areas, including online shopping, social media, and entertainment platforms. They are designed to help businesses reach their target audience more effectively.",{"uri":3334,"id":3335,"title":3336,"url":3337,"postDate":3338,"dateUpdated":3339,"slug":3340,"sectionHandle":373,"type":410,"authors":3341,"seo":3349,"categories":3357,"contentArea":3359,"siteName":371},"glossary/recurrent-neural-network","17953","Recurrent Neural Network","https://pixis-brand-web-1dfin.sevalla.page/glossary/recurrent-neural-network/","2025-03-06T07:27:21-05:00","2025-04-17T03:17:55-04:00","recurrent-neural-network",[3342],{"fullName":371,"asset":3343,"position":419,"bio":9,"linkedIn":9,"authorPage":3348},[3344],{"type":27,"image":3345,"mobileImage":3347},[3346],{"src":417,"alt":9},[],[],{"title":3350,"description":382,"advanced":3351,"keywords":3353,"social":3354},"Recurrent Neural Network | Pixis",{"canonical":9,"robots":3352},[],[],{"facebook":3355,"twitter":3356},{"description":382,"title":3350},{"description":382,"title":3350},[3358],{"title":1308,"slug":1309},[3360],{"blocks":3361},[3362],{"type":437,"textBlock":3363},"A Recurrent Neural Network (RNN) is a type of artificial neural network that has a loop in its architecture, allowing it to process sequences of data with the output being dependent on the previous computations. For example, in the sentence \"The cat sat on the mat,\" an RNN could use the hidden state to remember that \"the\" refers to a specific object, rather than just being a generic article. This allows the RNN to correctly translate the sentence into another language, even if the words are not in the same order as the original sentence.",{"uri":3365,"id":3366,"title":3367,"url":3368,"postDate":3369,"dateUpdated":3308,"slug":3370,"sectionHandle":373,"type":410,"authors":3371,"seo":3379,"categories":3387,"contentArea":3389,"siteName":371},"glossary/recursive-neural-network","17947","Recursive Neural Network","https://pixis-brand-web-1dfin.sevalla.page/glossary/recursive-neural-network/","2025-03-06T07:26:58-05:00","recursive-neural-network",[3372],{"fullName":371,"asset":3373,"position":419,"bio":9,"linkedIn":9,"authorPage":3378},[3374],{"type":27,"image":3375,"mobileImage":3377},[3376],{"src":417,"alt":9},[],[],{"title":3380,"description":382,"advanced":3381,"keywords":3383,"social":3384},"Recursive Neural Network | Pixis",{"canonical":9,"robots":3382},[],[],{"facebook":3385,"twitter":3386},{"description":382,"title":3380},{"description":382,"title":3380},[3388],{"title":1308,"slug":1309},[3390],{"blocks":3391},[3392],{"type":437,"textBlock":3393},"A Recursive Neural Network is a type of artificial neural network that takes a piece of data, analyzes it, and then uses that analysis to inform how it processes the next piece of data. This process is repeated until all of the data has been analyzed, and the network is able to draw conclusions and make predictions based on the patterns it has identified. Recursive Neural Networks are often used in tasks that require the analysis of complex, hierarchical data structures, such as Natural Language Processing (NLP), image recognition, and computer vision. They are particularly useful for tasks that involve analyzing the relationships between different pieces of data, as they are able to follow the logical structure of the data and identify patterns that may not be apparent to a traditional machine learning algorithm.",{"uri":3395,"id":3396,"title":3397,"url":3398,"postDate":3399,"dateUpdated":3277,"slug":3400,"sectionHandle":373,"type":410,"authors":3401,"seo":3409,"categories":3417,"contentArea":3419,"siteName":371},"glossary/reinforcement-learning","17965","Reinforcement Learning","https://pixis-brand-web-1dfin.sevalla.page/glossary/reinforcement-learning/","2025-03-06T07:28:12-05:00","reinforcement-learning",[3402],{"fullName":371,"asset":3403,"position":419,"bio":9,"linkedIn":9,"authorPage":3408},[3404],{"type":27,"image":3405,"mobileImage":3407},[3406],{"src":417,"alt":9},[],[],{"title":3410,"description":382,"advanced":3411,"keywords":3413,"social":3414},"Reinforcement Learning | Pixis",{"canonical":9,"robots":3412},[],[],{"facebook":3415,"twitter":3416},{"description":382,"title":3410},{"description":382,"title":3410},[3418],{"title":1308,"slug":1309},[3420],{"blocks":3421},[3422],{"type":437,"textBlock":3423},"Reinforcement Learning is a type of Artificial Intelligence (AI) training that involves training a machine to take actions in a specific environment in order to achieve a certain goal. It involves giving the computer rewards or punishments for certain actions in order to teach it how to make decisions that lead to the desired outcome. This is often done through trial and error, with the computer learning from its mistakes and adjusting its behavior accordingly. In this way, reinforcement learning allows AI systems to learn and adapt to new situations and environments, making them more versatile and efficient.",{"uri":3425,"id":3426,"title":3427,"url":3428,"postDate":3429,"dateUpdated":3277,"slug":3430,"sectionHandle":373,"type":410,"authors":3431,"seo":3439,"categories":3447,"contentArea":3449,"siteName":371},"glossary/resnet","17959","ResNet","https://pixis-brand-web-1dfin.sevalla.page/glossary/resnet/","2025-03-06T07:27:51-05:00","resnet",[3432],{"fullName":371,"asset":3433,"position":419,"bio":9,"linkedIn":9,"authorPage":3438},[3434],{"type":27,"image":3435,"mobileImage":3437},[3436],{"src":417,"alt":9},[],[],{"title":3440,"description":382,"advanced":3441,"keywords":3443,"social":3444},"ResNet | Pixis",{"canonical":9,"robots":3442},[],[],{"facebook":3445,"twitter":3446},{"description":382,"title":3440},{"description":382,"title":3440},[3448],{"title":1308,"slug":1309},[3450],{"blocks":3451},[3452],{"type":437,"textBlock":3453},"ResNet is a type of artificial neural network that is particularly useful for tasks that require a lot of processing power, such as image recognition or language translation. It works by breaking down a task into smaller pieces and then processing each piece separately, which makes it more efficient and accurate than other types of neural networks.\n\nThe Res in ResNet stands for Residual, which refers to a unique feature of this model. In most AI models, the data is processed through a series of interconnected layers, called neurons, that are designed to recognize specific patterns. However, in a ResNet model, the neurons are connected in such a way that some of the data is residual, meaning it is not processed through all of the layers. This allows the model to recognize patterns that are more complex or subtle, making it more accurate and efficient at tasks such as image or video recognition.",{"uri":3455,"id":3456,"title":3457,"url":3458,"postDate":3459,"dateUpdated":3460,"slug":3461,"sectionHandle":373,"type":410,"authors":3462,"seo":3470,"categories":3478,"contentArea":3480,"siteName":371},"glossary/self-supervised-learning-framework","17989","Self-Supervised Learning Framework","https://pixis-brand-web-1dfin.sevalla.page/glossary/self-supervised-learning-framework/","2025-03-06T07:29:49-05:00","2025-04-17T03:17:58-04:00","self-supervised-learning-framework",[3463],{"fullName":371,"asset":3464,"position":419,"bio":9,"linkedIn":9,"authorPage":3469},[3465],{"type":27,"image":3466,"mobileImage":3468},[3467],{"src":417,"alt":9},[],[],{"title":3471,"description":382,"advanced":3472,"keywords":3474,"social":3475},"Self-Supervised Learning Framework | Pixis",{"canonical":9,"robots":3473},[],[],{"facebook":3476,"twitter":3477},{"description":382,"title":3471},{"description":382,"title":3471},[3479],{"title":1308,"slug":1309},[3481],{"blocks":3482},[3483],{"type":437,"textBlock":3484},"Self-Supervised Learning is a type of machine learning in which the model is given a task to perform, but is not explicitly given the correct answers. Instead, the model must figure out how to solve the task on its own, using the input data as a guide. The Self-Supervised Learning Framework allows the model to learn more complex patterns and relationships in the data. Overall, it allows machines to learn and adapt in a more autonomous and flexible way.",{"uri":3486,"id":3487,"title":3488,"url":3489,"postDate":3490,"dateUpdated":3460,"slug":3491,"sectionHandle":373,"type":410,"authors":3492,"seo":3500,"categories":3508,"contentArea":3510,"siteName":371},"glossary/semantic-mapping","17983","Semantic Mapping","https://pixis-brand-web-1dfin.sevalla.page/glossary/semantic-mapping/","2025-03-06T07:29:24-05:00","semantic-mapping",[3493],{"fullName":371,"asset":3494,"position":419,"bio":9,"linkedIn":9,"authorPage":3499},[3495],{"type":27,"image":3496,"mobileImage":3498},[3497],{"src":417,"alt":9},[],[],{"title":3501,"description":382,"advanced":3502,"keywords":3504,"social":3505},"Semantic Mapping | Pixis",{"canonical":9,"robots":3503},[],[],{"facebook":3506,"twitter":3507},{"description":382,"title":3501},{"description":382,"title":3501},[3509],{"title":1308,"slug":1309},[3511],{"blocks":3512},[3513],{"type":437,"textBlock":3514},"Semantic Mapping in the context of Artificial Intelligence (AI) refers to the process of assigning meaning to different elements or concepts within a system. This can involve mapping words or phrases to specific definitions or concepts, or it can involve linking related ideas or concepts together in a way that allows an AI system to understand and interpret them more effectively. Semantic Mapping is an important aspect of Natural Language Processing (NLP) and machine learning, as it helps to make sense of large amounts of data and allows AI systems to communicate more effectively with humans.",{"uri":3516,"id":3517,"title":3518,"url":3519,"postDate":3520,"dateUpdated":3521,"slug":3522,"sectionHandle":373,"type":410,"authors":3523,"seo":3531,"categories":3539,"contentArea":3541,"siteName":371},"glossary/sentiment-analysis","17977","Sentiment Analysis","https://pixis-brand-web-1dfin.sevalla.page/glossary/sentiment-analysis/","2025-03-06T07:28:55-05:00","2025-04-17T03:17:57-04:00","sentiment-analysis",[3524],{"fullName":371,"asset":3525,"position":419,"bio":9,"linkedIn":9,"authorPage":3530},[3526],{"type":27,"image":3527,"mobileImage":3529},[3528],{"src":417,"alt":9},[],[],{"title":3532,"description":382,"advanced":3533,"keywords":3535,"social":3536},"Sentiment Analysis | Pixis",{"canonical":9,"robots":3534},[],[],{"facebook":3537,"twitter":3538},{"description":382,"title":3532},{"description":382,"title":3532},[3540],{"title":1308,"slug":1309},[3542],{"blocks":3543},[3544],{"type":437,"textBlock":3545},"Sentiment Analysis is a way for Artificial Intelligence (AI) to analyze and understand the underlying emotions and opinions of words and language. For example, if someone writes a review of a product and they say they love it, the AI can recognize that the person has a positive sentiment towards the product. On the other hand, if someone writes a review saying they hate the product, the AI can recognize that the person has a negative sentiment. This can be helpful for businesses to understand how people feel about their products or services and make improvements or changes based on customer feedback.",{"uri":3547,"id":3548,"title":3549,"url":3550,"postDate":3551,"dateUpdated":3552,"slug":3553,"sectionHandle":373,"type":410,"authors":3554,"seo":3562,"categories":3570,"contentArea":3572,"siteName":371},"glossary/style-transfer","17995","Style Transfer","https://pixis-brand-web-1dfin.sevalla.page/glossary/style-transfer/","2025-03-06T07:30:16-05:00","2025-04-17T03:17:59-04:00","style-transfer",[3555],{"fullName":371,"asset":3556,"position":419,"bio":9,"linkedIn":9,"authorPage":3561},[3557],{"type":27,"image":3558,"mobileImage":3560},[3559],{"src":417,"alt":9},[],[],{"title":3563,"description":382,"advanced":3564,"keywords":3566,"social":3567},"Style Transfer | Pixis",{"canonical":9,"robots":3565},[],[],{"facebook":3568,"twitter":3569},{"description":382,"title":3563},{"description":382,"title":3563},[3571],{"title":1308,"slug":1309},[3573],{"blocks":3574},[3575],{"type":437,"textBlock":3576},"Style Transfer is a process in which the style of one image is applied to another image, creating a new and unique image. It is used by AI to enhance the creative potential of digital images and help people create beautiful and unique works of art. AI algorithms are able to understand the unique characteristics and features of an image's style, such as brushstrokes, color palette, and texture, and apply these characteristics to the other image. Style Transfer is used in marketing to create unique and creative images without having to spend a lot of time and effort on manual editing, or to match the style of a brand's existing aesthetic.",{"uri":3578,"id":3579,"title":3580,"url":3581,"postDate":3582,"dateUpdated":3552,"slug":3583,"sectionHandle":373,"type":410,"authors":3584,"seo":3592,"categories":3600,"contentArea":3602,"siteName":371},"glossary/supervised-learning","18001","Supervised Learning","https://pixis-brand-web-1dfin.sevalla.page/glossary/supervised-learning/","2025-03-06T07:30:50-05:00","supervised-learning",[3585],{"fullName":371,"asset":3586,"position":419,"bio":9,"linkedIn":9,"authorPage":3591},[3587],{"type":27,"image":3588,"mobileImage":3590},[3589],{"src":417,"alt":9},[],[],{"title":3593,"description":382,"advanced":3594,"keywords":3596,"social":3597},"Supervised Learning | Pixis",{"canonical":9,"robots":3595},[],[],{"facebook":3598,"twitter":3599},{"description":382,"title":3593},{"description":382,"title":3593},[3601],{"title":1308,"slug":1309},[3603],{"blocks":3604},[3605],{"type":437,"textBlock":3606},"Supervised Learning is a type of machine learning that involves training a machine model on a dataset that has already been labeled or classified with the correct output or response. The computer is then trained to recognize patterns and relationships within the data and use that knowledge to make predictions about new data. Once the model has learned these patterns, we can then give it new, unlabeled images and it should be able to correctly identify the type based on patterns it learned during training. Supervised Learning is a powerful tool for automating tasks that require making decisions based on data, such as predicting outcomes, classifying objects, or detecting patterns.",{"uri":3608,"id":3609,"title":3610,"url":3611,"postDate":3612,"dateUpdated":3613,"slug":3614,"sectionHandle":373,"type":410,"authors":3615,"seo":3623,"categories":3631,"contentArea":3633,"siteName":371},"glossary/target-daily-results","18031","Target Daily Results","https://pixis-brand-web-1dfin.sevalla.page/glossary/target-daily-results/","2025-03-06T07:33:22-05:00","2025-04-17T03:18:03-04:00","target-daily-results",[3616],{"fullName":371,"asset":3617,"position":419,"bio":9,"linkedIn":9,"authorPage":3622},[3618],{"type":27,"image":3619,"mobileImage":3621},[3620],{"src":417,"alt":9},[],[],{"title":3624,"description":382,"advanced":3625,"keywords":3627,"social":3628},"Target Daily Results | Pixis",{"canonical":9,"robots":3626},[],[],{"facebook":3629,"twitter":3630},{"description":382,"title":3624},{"description":382,"title":3624},[3632],{"title":1308,"slug":1309},[3634],{"blocks":3635},[3636],{"type":437,"textBlock":3637},"Target Daily Results is a term that refers to the goals or objectives that an Artificial Intelligence (AI) system is designed to achieve on a daily basis. These goals can vary widely depending on the specific application of the AI system. They might include things such as improving efficiency, increasing profits, providing better services or products to customers, making predictions or recommendations, or automating certain tasks or processes. For Pixis, the Target Daily Results would be the specific outcomes that the AI system is intended to achieve on a daily basis, such as providing accurate budget distribution recommendations or increasing return on ad spend through personalized recommendations.",{"uri":3639,"id":3640,"title":3641,"url":3642,"postDate":3643,"dateUpdated":3644,"slug":3645,"sectionHandle":373,"type":410,"authors":3646,"seo":3654,"categories":3662,"contentArea":3664,"siteName":371},"glossary/target-cost-per-optimization-event","18025","Target-Cost Per Optimization Event","https://pixis-brand-web-1dfin.sevalla.page/glossary/target-cost-per-optimization-event/","2025-03-06T07:32:59-05:00","2025-04-17T03:18:02-04:00","target-cost-per-optimization-event",[3647],{"fullName":371,"asset":3648,"position":419,"bio":9,"linkedIn":9,"authorPage":3653},[3649],{"type":27,"image":3650,"mobileImage":3652},[3651],{"src":417,"alt":9},[],[],{"title":3655,"description":382,"advanced":3656,"keywords":3658,"social":3659},"Target-Cost Per Optimization Event | Pixis",{"canonical":9,"robots":3657},[],[],{"facebook":3660,"twitter":3661},{"description":382,"title":3655},{"description":382,"title":3655},[3663],{"title":1308,"slug":1309},[3665],{"blocks":3666},[3667],{"type":437,"textBlock":3668},"The Target-Cost per Optimization Event refers to the desired cost of using Artificial Intelligence (AI) to optimize a specific task or process. This cost may be measured in terms of financial resources, time, or other resources. In the context of AI, optimization refers to the process of improving the efficiency, accuracy, or effectiveness of a task or process by using Artificial Intelligence techniques such as machine learning, natural language processing, or computer vision. The Target-ost per Optimization Event may be used to guide the development and deployment of AI systems, and to assess the value and cost-effectiveness of these systems in different contexts.",{"uri":3670,"id":3671,"title":3672,"url":3673,"postDate":3674,"dateUpdated":3675,"slug":3676,"sectionHandle":373,"type":410,"authors":3677,"seo":3685,"categories":3693,"contentArea":3695,"siteName":371},"glossary/testing-dataset","18019","Testing Dataset","https://pixis-brand-web-1dfin.sevalla.page/glossary/testing-dataset/","2025-03-06T07:32:21-05:00","2025-04-17T03:18:01-04:00","testing-dataset",[3678],{"fullName":371,"asset":3679,"position":419,"bio":9,"linkedIn":9,"authorPage":3684},[3680],{"type":27,"image":3681,"mobileImage":3683},[3682],{"src":417,"alt":9},[],[],{"title":3686,"description":382,"advanced":3687,"keywords":3689,"social":3690},"Testing Dataset | Pixis",{"canonical":9,"robots":3688},[],[],{"facebook":3691,"twitter":3692},{"description":382,"title":3686},{"description":382,"title":3686},[3694],{"title":1308,"slug":1309},[3696],{"blocks":3697},[3698],{"type":437,"textBlock":3699},"A Testing Dataset is a set of data that is used to evaluate the performance of an AI model. It is used to determine how well the model is able to make predictions or decisions based on the data it has been trained on. It is usually a smaller, representative data sample in comparison to the training dataset used to simulate real-world situations to test the model's accuracy and reliability. The purpose of the Testing Dataset is to provide a realistic evaluation of the AI model's performance and to help identify any weaknesses or areas for improvement. It helps ensure that the AI model is reliable and effective before it is deployed in real-world applications.",{"uri":3701,"id":3702,"title":3703,"url":3704,"postDate":3705,"dateUpdated":3706,"slug":3707,"sectionHandle":373,"type":410,"authors":3708,"seo":3716,"categories":3724,"contentArea":3726,"siteName":371},"glossary/training-dataset","18013","Training Dataset","https://pixis-brand-web-1dfin.sevalla.page/glossary/training-dataset/","2025-03-06T07:31:46-05:00","2025-04-17T03:18:00-04:00","training-dataset",[3709],{"fullName":371,"asset":3710,"position":419,"bio":9,"linkedIn":9,"authorPage":3715},[3711],{"type":27,"image":3712,"mobileImage":3714},[3713],{"src":417,"alt":9},[],[],{"title":3717,"description":382,"advanced":3718,"keywords":3720,"social":3721},"Training Dataset | Pixis",{"canonical":9,"robots":3719},[],[],{"facebook":3722,"twitter":3723},{"description":382,"title":3717},{"description":382,"title":3717},[3725],{"title":1308,"slug":1309},[3727],{"blocks":3728},[3729],{"type":437,"textBlock":3730},"A Training Dataset is a collection of data that is used to teach a machine learning model how to perform a particular task. This dataset is used to train the model to recognize patterns and make predictions or decisions based on those patterns. For example, if you want to teach a model to recognize pictures of dogs, you would provide it with a training dataset that consists of hundreds or thousands of pictures of dogs.",{"uri":3732,"id":3733,"title":3734,"url":3735,"postDate":3736,"dateUpdated":3552,"slug":3737,"sectionHandle":373,"type":410,"authors":3738,"seo":3746,"categories":3754,"contentArea":3756,"siteName":371},"glossary/transfer-learning","18007","Transfer Learning","https://pixis-brand-web-1dfin.sevalla.page/glossary/transfer-learning/","2025-03-06T07:31:17-05:00","transfer-learning",[3739],{"fullName":371,"asset":3740,"position":419,"bio":9,"linkedIn":9,"authorPage":3745},[3741],{"type":27,"image":3742,"mobileImage":3744},[3743],{"src":417,"alt":9},[],[],{"title":3747,"description":382,"advanced":3748,"keywords":3750,"social":3751},"Transfer Learning | Pixis",{"canonical":9,"robots":3749},[],[],{"facebook":3752,"twitter":3753},{"description":382,"title":3747},{"description":382,"title":3747},[3755],{"title":1308,"slug":1309},[3757],{"blocks":3758},[3759],{"type":437,"textBlock":3760},"Transfer Learning is a machine learning technique that involves taking a pre-trained model developed for a task and adapting it for use on a new and different task. This can be especially useful when the new task is similar to the original task, or when there is a shortage of data or resources to train a model from scratch. It also allows us to leverage the knowledge learned by a model on one task and apply it to a new task, potentially improving the performance of the new model.",{"uri":3762,"id":3763,"title":3764,"url":3765,"postDate":3766,"dateUpdated":3613,"slug":3767,"sectionHandle":373,"type":410,"authors":3768,"seo":3776,"categories":3784,"contentArea":3786,"siteName":371},"glossary/unsupervised-learning","18037","Unsupervised Learning","https://pixis-brand-web-1dfin.sevalla.page/glossary/unsupervised-learning/","2025-03-06T07:33:46-05:00","unsupervised-learning",[3769],{"fullName":371,"asset":3770,"position":419,"bio":9,"linkedIn":9,"authorPage":3775},[3771],{"type":27,"image":3772,"mobileImage":3774},[3773],{"src":417,"alt":9},[],[],{"title":3777,"description":382,"advanced":3778,"keywords":3780,"social":3781},"Unsupervised Learning | Pixis",{"canonical":9,"robots":3779},[],[],{"facebook":3782,"twitter":3783},{"description":382,"title":3777},{"description":382,"title":3777},[3785],{"title":1308,"slug":1309},[3787],{"blocks":3788},[3789],{"type":437,"textBlock":3790},"Unsupervised learning is a type of machine learning where the model is not given any labeled training data or feedback on its performance. Instead, it’s given a dataset and is asked to learn patterns and relationships within the data on its own. This is in contrast to supervised learning, where the model is given labeled training examples and is trained to make predictions based on those examples. Unsupervised learning can be used for a variety of tasks, such as clustering data points into groups, detecting anomalies or outliers in the data, and finding hidden patterns or relationships within the data.",{"uri":3792,"id":3793,"title":3794,"url":3795,"postDate":3796,"dateUpdated":3797,"slug":3798,"sectionHandle":373,"type":410,"authors":3799,"seo":3807,"categories":3815,"contentArea":3817,"siteName":371},"glossary/variational-auto-encoders-vaes","18043","Variational Auto Encoders (VAEs)","https://pixis-brand-web-1dfin.sevalla.page/glossary/variational-auto-encoders-vaes/","2025-03-06T07:34:19-05:00","2025-04-17T03:18:04-04:00","variational-auto-encoders-vaes",[3800],{"fullName":371,"asset":3801,"position":419,"bio":9,"linkedIn":9,"authorPage":3806},[3802],{"type":27,"image":3803,"mobileImage":3805},[3804],{"src":417,"alt":9},[],[],{"title":3808,"description":382,"advanced":3809,"keywords":3811,"social":3812},"Variational Auto Encoders (VAEs) | Pixis",{"canonical":9,"robots":3810},[],[],{"facebook":3813,"twitter":3814},{"description":382,"title":3808},{"description":382,"title":3808},[3816],{"title":1308,"slug":1309},[3818],{"blocks":3819},[3820],{"type":437,"textBlock":3821},"\u003Cspan style=\"font-weight:400;\">Variational Autoencoders (VAEs) are generative models that are used to learn and generate new data samples, typically in the form of images, but they can be applied to other types of data as well. It consists of an encoder and a decoder. The encoder compresses the input data into a lower-dimensional representation, called the latent space or code. The decoder then reconstructs the original input data from the compressed representation.\u003C/span>",1775681195638]