{"id":257,"count":0,"description":"","link":"https:\/\/tenjin.com\/es\/glossary\/aggregation\/","name":"Aggregation","slug":"aggregation","taxonomy":"glossaries","parent":0,"meta":{"status":["1"],"order":["0"],"glossary_term_description":["<div style=\"border: 1px solid #e5e5e5;padding: 16px;border-radius: 8px;background: #fafafa\">\r\n\r\n<b>Definition:<\/b>\r\n\r\n<span style=\"font-weight: 400\">Aggregation in mobile analytics is the process of combining data from multiple sources into a single, unified view. It applies to ad spend, attribution outcomes, monetization data, and user behavior. Aggregation is what makes it possible for growth teams to compare performance across channels, calculate blended metrics, and make informed decisions without managing fragmented reports from each individual source.\r\n<\/span>\r\n\r\n<\/div>\r\n&nbsp;\r\n<h2><b>What is Aggregation in Mobile Analytics?<\/b><\/h2>\r\n<span style=\"font-weight: 400\">In mobile analytics and advertising, aggregation refers to the process of collecting, combining, and summarizing data from multiple sources into a single, unified view. Rather than analyzing data in isolated silos, aggregation brings different data points together so teams can understand performance across the full picture.<\/span>\r\n\r\n<span style=\"font-weight: 400\">Aggregation is a foundational concept in mobile measurement. Attribution platforms, analytics dashboards, and reporting tools all rely on some form of aggregation to make data usable at scale.<\/span>\r\n<h2><b>What Gets Aggregated<\/b><\/h2>\r\n<span style=\"font-weight: 400\">In mobile app analytics and user acquisition, aggregation commonly applies to:<\/span>\r\n<ul>\r\n \t<li style=\"font-weight: 400\"><b>Ad spend data:<\/b><span style=\"font-weight: 400\"> Combining cost figures from multiple ad networks (see: cost aggregation)<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><b>Attribution data:<\/b><span style=\"font-weight: 400\"> Summarizing installs, events, and revenue across campaigns, networks, and time periods<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><b>Monetization data:<\/b><span style=\"font-weight: 400\"> Combining in-app purchase revenue and ad revenue from multiple sources into a single revenue view<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><b>User data:<\/b><span style=\"font-weight: 400\"> Grouping users into cohorts based on install date, channel, or behavior for analysis<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><b>Campaign data:<\/b><span style=\"font-weight: 400\"> Rolling up performance metrics like impressions, clicks, installs, and ROAS across ad sets and campaigns<\/span><\/li>\r\n<\/ul>\r\n<h2><b>How Aggregation Works in Practice<\/b><\/h2>\r\n<span style=\"font-weight: 400\">Data aggregation typically happens at the platform level, where the analytics or attribution tool collects raw data from multiple sources (ad networks, SDKs, APIs, and internal systems) and processes it into structured reports.<\/span>\r\n\r\n<span style=\"font-weight: 400\">For example, a mobile team running campaigns on five different networks might see:<\/span>\r\n<ul>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Five separate cost reports from each network<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Five different sets of attribution data<\/span><\/li>\r\n<\/ul>\r\n<span style=\"font-weight: 400\">Aggregation combines these into a single dashboard view, where the team can see total spend, total installs, and blended ROAS across all five networks without manually compiling anything.<\/span>\r\n<h3><\/h3>\r\n<h2><b>Aggregated Data vs. Raw Data<\/b><\/h2>\r\n&nbsp;\r\n\r\n<span style=\"font-weight: 400\">It is useful to understand the difference between aggregated data and raw data:<\/span>\r\n<ul>\r\n \t<li style=\"font-weight: 400\"><b>Raw data<\/b><span style=\"font-weight: 400\"> is individual-level or event-level data that has not been processed or summarized. It contains the most granular detail but requires more work to analyze.<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><b>Aggregated data<\/b><span style=\"font-weight: 400\"> is summarized across a defined dimension, such as campaign, date, country, or ad network. It is easier to read and compare but may obscure patterns that only appear at the raw level.<\/span><\/li>\r\n<\/ul>\r\n<span style=\"font-weight: 400\">Both have their place. Aggregated data is useful for dashboards and high-level reporting. Raw data is useful for deeper analysis, custom reporting, and building data pipelines. Tools like Tenjin's DataVault and Raw Data Exporter support teams that need access to both.<\/span>\r\n<h2><b>Aggregation and Privacy<\/b><\/h2>\r\n<span style=\"font-weight: 400\">In the context of mobile measurement, aggregation also has a specific meaning related to user privacy. Privacy frameworks such as Apple's SKAdNetwork (SKAN) use aggregated reporting by design, meaning individual user-level data is not passed back to advertisers. Instead, campaign performance is reported as aggregated conversion data.<\/span>\r\n\r\n<span style=\"font-weight: 400\">This type of privacy-preserving aggregation is increasingly common across the mobile ecosystem and requires analytics platforms to work with summarized signals rather than individual user events.<\/span>\r\n<h2><b>Why Aggregation Matters for Growth Teams<\/b><\/h2>\r\n<span style=\"font-weight: 400\">Without aggregation, mobile growth teams face a fragmented data environment. Data lives across networks, platforms, and tools, in different formats and at different levels of detail. Aggregation makes it possible to:<\/span>\r\n<ul>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Compare performance across channels in a single view<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Report on total spend, revenue, and ROAS accurately<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Spot trends and anomalies that would not be visible in siloed data<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Make faster, better-informed decisions<\/span><\/li>\r\n<\/ul>\r\n\r\n<hr \/>\r\n\r\n<h2><b>Related Terms<\/b><\/h2>\r\n<ul>\r\n \t<li><a href=\"https:\/\/tenjin.com\/glossary\/cost-aggregation\/\"><span style=\"font-weight: 400\">Cost Aggregation<\/span><\/a><\/li>\r\n \t<li><a href=\"https:\/\/tenjin.com\/glossary\/granular-raw-data\/\"><span style=\"font-weight: 400\">Granular \/ Raw Data<\/span><\/a><\/li>\r\n \t<li><a href=\"https:\/\/tenjin.com\/glossary\/attribution\/\"><span style=\"font-weight: 400\">Attribution<\/span><\/a><\/li>\r\n \t<li><a href=\"https:\/\/tenjin.com\/glossary\/skad-network\/\"><span style=\"font-weight: 400\">SKAdNetwork<\/span><\/a><\/li>\r\n \t<li><a href=\"https:\/\/tenjin.com\/glossary\/mobile-marketing-metrics\/\"><span style=\"font-weight: 400\">Mobile Marketing Metrics<\/span><\/a><\/li>\r\n \t<li><span style=\"font-weight: 400\"><a href=\"https:\/\/tenjin.com\/glossary\/datavault\/\">DataVault<\/a><\/span><\/li>\r\n<\/ul>\r\n\r\n<hr \/>\r\n\r\n<h2><b>Frequently Asked Questions About Aggregation<\/b><\/h2>\r\n<b>What does aggregation mean in mobile analytics?<\/b><span style=\"font-weight: 400\"> Aggregation means combining data from multiple sources or dimensions into a single summarized view. In mobile analytics, this typically applies to ad spend, attribution data, monetization data, and campaign performance.<\/span>\r\n\r\n<b>Why is data aggregation important for mobile growth teams?<\/b><span style=\"font-weight: 400\"> Mobile campaigns run across many networks and platforms. Without aggregation, teams work with fragmented data that is hard to compare. Aggregation creates a single view of performance so teams can make faster and more accurate decisions.<\/span>\r\n\r\n<b>What is the difference between aggregated data and raw data?<\/b><span style=\"font-weight: 400\"> Raw data is individual or event-level data in its unprocessed form. Aggregated data has been summarized across a dimension such as campaign, date, or country. Raw data provides more granularity. Aggregated data is easier to read and compare at a high level.<\/span>\r\n\r\n<b>How does aggregation relate to attribution?<\/b><span style=\"font-weight: 400\"> Attribution platforms aggregate installs, events, and revenue by campaign, network, or channel so teams can see which sources are driving results. This aggregated attribution view is what connects spend data to outcomes.<\/span>\r\n\r\n<b>What is privacy-preserving aggregation?<\/b><span style=\"font-weight: 400\"> Privacy-preserving aggregation means reporting campaign performance as summarized data rather than individual user-level events. Apple's SKAdNetwork uses this approach. Aggregated signals protect user privacy while still giving advertisers a view of campaign-level performance.<\/span>\r\n\r\n<b>What is the difference between aggregation and cost aggregation?<\/b><span style=\"font-weight: 400\"> Cost aggregation is a specific type of aggregation focused on ad spend data. General data aggregation covers any type of performance data, including installs, events, revenue, and user behavior. Cost aggregation is one part of a broader aggregation strategy.<\/span>\r\n\r\n<b>How does Tenjin support data aggregation?<\/b><span style=\"font-weight: 400\"> Tenjin's dashboard aggregates attribution, cost, and monetization data across sources so teams can see performance in one place. For teams that need to go deeper, DataVault and Raw Data Exporter provide access to granular and raw data for custom analysis.<\/span>"]},"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Aggregation in Mobile Analytics: What It Means and Why It Matter<\/title>\n<meta name=\"description\" content=\"Data aggregation combines performance data from multiple sources into a single view. 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It applies to ad spend, attribution outcomes, monetization data, and user behavior. Aggregation is what makes it possible for growth teams to compare performance across channels, calculate blended metrics, and make informed decisions without managing fragmented reports from each individual source.\r\n<\/span>\r\n\r\n<\/div>\r\n&nbsp;\r\n<h2><b>What is Aggregation in Mobile Analytics?<\/b><\/h2>\r\n<span style=\"font-weight: 400\">In mobile analytics and advertising, aggregation refers to the process of collecting, combining, and summarizing data from multiple sources into a single, unified view. Rather than analyzing data in isolated silos, aggregation brings different data points together so teams can understand performance across the full picture.<\/span>\r\n\r\n<span style=\"font-weight: 400\">Aggregation is a foundational concept in mobile measurement. Attribution platforms, analytics dashboards, and reporting tools all rely on some form of aggregation to make data usable at scale.<\/span>\r\n<h2><b>What Gets Aggregated<\/b><\/h2>\r\n<span style=\"font-weight: 400\">In mobile app analytics and user acquisition, aggregation commonly applies to:<\/span>\r\n<ul>\r\n \t<li style=\"font-weight: 400\"><b>Ad spend data:<\/b><span style=\"font-weight: 400\"> Combining cost figures from multiple ad networks (see: cost aggregation)<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><b>Attribution data:<\/b><span style=\"font-weight: 400\"> Summarizing installs, events, and revenue across campaigns, networks, and time periods<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><b>Monetization data:<\/b><span style=\"font-weight: 400\"> Combining in-app purchase revenue and ad revenue from multiple sources into a single revenue view<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><b>User data:<\/b><span style=\"font-weight: 400\"> Grouping users into cohorts based on install date, channel, or behavior for analysis<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><b>Campaign data:<\/b><span style=\"font-weight: 400\"> Rolling up performance metrics like impressions, clicks, installs, and ROAS across ad sets and campaigns<\/span><\/li>\r\n<\/ul>\r\n<h2><b>How Aggregation Works in Practice<\/b><\/h2>\r\n<span style=\"font-weight: 400\">Data aggregation typically happens at the platform level, where the analytics or attribution tool collects raw data from multiple sources (ad networks, SDKs, APIs, and internal systems) and processes it into structured reports.<\/span>\r\n\r\n<span style=\"font-weight: 400\">For example, a mobile team running campaigns on five different networks might see:<\/span>\r\n<ul>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Five separate cost reports from each network<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Five different sets of attribution data<\/span><\/li>\r\n<\/ul>\r\n<span style=\"font-weight: 400\">Aggregation combines these into a single dashboard view, where the team can see total spend, total installs, and blended ROAS across all five networks without manually compiling anything.<\/span>\r\n<h3><\/h3>\r\n<h2><b>Aggregated Data vs. Raw Data<\/b><\/h2>\r\n&nbsp;\r\n\r\n<span style=\"font-weight: 400\">It is useful to understand the difference between aggregated data and raw data:<\/span>\r\n<ul>\r\n \t<li style=\"font-weight: 400\"><b>Raw data<\/b><span style=\"font-weight: 400\"> is individual-level or event-level data that has not been processed or summarized. It contains the most granular detail but requires more work to analyze.<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><b>Aggregated data<\/b><span style=\"font-weight: 400\"> is summarized across a defined dimension, such as campaign, date, country, or ad network. It is easier to read and compare but may obscure patterns that only appear at the raw level.<\/span><\/li>\r\n<\/ul>\r\n<span style=\"font-weight: 400\">Both have their place. Aggregated data is useful for dashboards and high-level reporting. Raw data is useful for deeper analysis, custom reporting, and building data pipelines. Tools like Tenjin's DataVault and Raw Data Exporter support teams that need access to both.<\/span>\r\n<h2><b>Aggregation and Privacy<\/b><\/h2>\r\n<span style=\"font-weight: 400\">In the context of mobile measurement, aggregation also has a specific meaning related to user privacy. Privacy frameworks such as Apple's SKAdNetwork (SKAN) use aggregated reporting by design, meaning individual user-level data is not passed back to advertisers. Instead, campaign performance is reported as aggregated conversion data.<\/span>\r\n\r\n<span style=\"font-weight: 400\">This type of privacy-preserving aggregation is increasingly common across the mobile ecosystem and requires analytics platforms to work with summarized signals rather than individual user events.<\/span>\r\n<h2><b>Why Aggregation Matters for Growth Teams<\/b><\/h2>\r\n<span style=\"font-weight: 400\">Without aggregation, mobile growth teams face a fragmented data environment. Data lives across networks, platforms, and tools, in different formats and at different levels of detail. Aggregation makes it possible to:<\/span>\r\n<ul>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Compare performance across channels in a single view<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Report on total spend, revenue, and ROAS accurately<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Spot trends and anomalies that would not be visible in siloed data<\/span><\/li>\r\n \t<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Make faster, better-informed decisions<\/span><\/li>\r\n<\/ul>\r\n\r\n<hr \/>\r\n\r\n<h2><b>Related Terms<\/b><\/h2>\r\n<ul>\r\n \t<li><a href=\"https:\/\/tenjin.com\/glossary\/cost-aggregation\/\"><span style=\"font-weight: 400\">Cost Aggregation<\/span><\/a><\/li>\r\n \t<li><a href=\"https:\/\/tenjin.com\/glossary\/granular-raw-data\/\"><span style=\"font-weight: 400\">Granular \/ Raw Data<\/span><\/a><\/li>\r\n \t<li><a href=\"https:\/\/tenjin.com\/glossary\/attribution\/\"><span style=\"font-weight: 400\">Attribution<\/span><\/a><\/li>\r\n \t<li><a href=\"https:\/\/tenjin.com\/glossary\/skad-network\/\"><span style=\"font-weight: 400\">SKAdNetwork<\/span><\/a><\/li>\r\n \t<li><a href=\"https:\/\/tenjin.com\/glossary\/mobile-marketing-metrics\/\"><span style=\"font-weight: 400\">Mobile Marketing Metrics<\/span><\/a><\/li>\r\n \t<li><span style=\"font-weight: 400\"><a href=\"https:\/\/tenjin.com\/glossary\/datavault\/\">DataVault<\/a><\/span><\/li>\r\n<\/ul>\r\n\r\n<hr \/>\r\n\r\n<h2><b>Frequently Asked Questions About Aggregation<\/b><\/h2>\r\n<b>What does aggregation mean in mobile analytics?<\/b><span style=\"font-weight: 400\"> Aggregation means combining data from multiple sources or dimensions into a single summarized view. In mobile analytics, this typically applies to ad spend, attribution data, monetization data, and campaign performance.<\/span>\r\n\r\n<b>Why is data aggregation important for mobile growth teams?<\/b><span style=\"font-weight: 400\"> Mobile campaigns run across many networks and platforms. Without aggregation, teams work with fragmented data that is hard to compare. Aggregation creates a single view of performance so teams can make faster and more accurate decisions.<\/span>\r\n\r\n<b>What is the difference between aggregated data and raw data?<\/b><span style=\"font-weight: 400\"> Raw data is individual or event-level data in its unprocessed form. Aggregated data has been summarized across a dimension such as campaign, date, or country. Raw data provides more granularity. Aggregated data is easier to read and compare at a high level.<\/span>\r\n\r\n<b>How does aggregation relate to attribution?<\/b><span style=\"font-weight: 400\"> Attribution platforms aggregate installs, events, and revenue by campaign, network, or channel so teams can see which sources are driving results. This aggregated attribution view is what connects spend data to outcomes.<\/span>\r\n\r\n<b>What is privacy-preserving aggregation?<\/b><span style=\"font-weight: 400\"> Privacy-preserving aggregation means reporting campaign performance as summarized data rather than individual user-level events. Apple's SKAdNetwork uses this approach. Aggregated signals protect user privacy while still giving advertisers a view of campaign-level performance.<\/span>\r\n\r\n<b>What is the difference between aggregation and cost aggregation?<\/b><span style=\"font-weight: 400\"> Cost aggregation is a specific type of aggregation focused on ad spend data. General data aggregation covers any type of performance data, including installs, events, revenue, and user behavior. Cost aggregation is one part of a broader aggregation strategy.<\/span>\r\n\r\n<b>How does Tenjin support data aggregation?<\/b><span style=\"font-weight: 400\"> Tenjin's dashboard aggregates attribution, cost, and monetization data across sources so teams can see performance in one place. For teams that need to go deeper, DataVault and Raw Data Exporter provide access to granular and raw data for custom analysis.<\/span>","_links":{"self":[{"href":"https:\/\/tenjin.com\/es\/wp-json\/wp\/v2\/glossaries\/257","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tenjin.com\/es\/wp-json\/wp\/v2\/glossaries"}],"about":[{"href":"https:\/\/tenjin.com\/es\/wp-json\/wp\/v2\/taxonomies\/glossaries"}],"wp:post_type":[{"href":"https:\/\/tenjin.com\/es\/wp-json\/wp\/v2\/docs?glossaries=257"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}