{"id":58484,"date":"2026-05-21T20:10:25","date_gmt":"2026-05-21T17:10:25","guid":{"rendered":"https:\/\/affisemmp.com\/?post_type=glossary-term&#038;p=58484"},"modified":"2026-09-08T11:51:02","modified_gmt":"2026-09-08T08:51:02","slug":"cohort-analysis","status":"publish","type":"glossary-term","link":"https:\/\/affisemmp.com\/es\/glossary-term\/cohort-analysis\/","title":{"rendered":"Cohort Analysis"},"content":{"rendered":"<h2 data-path-to-node=\"3\"><strong>Cohort Analysis Definition<\/strong><\/h2>\n<p data-path-to-node=\"4\"><b data-path-to-node=\"4\" data-index-in-node=\"0\">Cohort analysis<\/b> is a powerful analytical method used in mobile marketing that involves grouping users based on shared characteristics\u2014such as their install date, acquisition source, or specific in-app behaviors\u2014and tracking their performance over a defined period of time.<\/p>\n<p data-path-to-node=\"5\">Instead of looking at your entire user base as one massive aggregate, cohort analysis lets you break complex data into smaller, digestible segments (\u00abcohorts\u00bb). By doing so, marketers and app developers can measure long-term user retention, engagement, and monetization patterns to see exactly what drives real growth.<\/p>\n<h2 data-path-to-node=\"6\"><strong>How Does Cohort Analysis Work in an MMP?<\/strong><\/h2>\n<p data-path-to-node=\"7\">In the context of a Mobile Measurement Partner (MMP) like <b data-path-to-node=\"7\" data-index-in-node=\"58\">Affise<\/b>, cohort analysis is the backbone of user acquisition (UA) optimization. An MMP tracks where your users come from (attribution) and what they do once they open the app (in-app events).<\/p>\n<p data-path-to-node=\"8\">By analyzing cohorts, you compare \u00abapples to apples.\u00bb For instance, you can compare the Day 7 retention rate of users acquired via a Facebook ad in January versus users acquired via a Google ad in February.<\/p>\n<h3 data-path-to-node=\"9\">1. Acquisition Cohorts<\/h3>\n<p data-path-to-node=\"10\">These cohorts group users by <i data-path-to-node=\"10\" data-index-in-node=\"29\">when<\/i> and <i data-path-to-node=\"10\" data-index-in-node=\"38\">where<\/i> they joined your app.<\/p>\n<ul data-path-to-node=\"11\">\n<li>\n<p data-path-to-node=\"11,0,0\"><b data-path-to-node=\"11,0,0\" data-index-in-node=\"0\">Time-based:<\/b> Users who installed the app during a specific day, week, or month (e.g., all users who downloaded the app on Black Friday).<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"11,1,0\"><b data-path-to-node=\"11,1,0\" data-index-in-node=\"0\">Source-based:<\/b> Users segmented by the marketing channel, campaign, or ad creative that brought them in (e.g., organic search vs. paid TikTok ads).<\/p>\n<\/li>\n<\/ul>\n<h3 data-path-to-node=\"12\">2. Behavioral Cohorts<\/h3>\n<p data-path-to-node=\"13\">These cohorts group users by the specific actions they take <i data-path-to-node=\"13\" data-index-in-node=\"60\">inside<\/i> the app.<\/p>\n<ul data-path-to-node=\"14\">\n<li>\n<p data-path-to-node=\"14,0,0\">Users who completed the onboarding tutorial.<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"14,1,0\">Users who made their first in-app purchase within 24 hours of installing.<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"14,2,0\">Users who abandon a shopping cart at checkout.<\/p>\n<\/li>\n<\/ul>\n<h2 data-path-to-node=\"17\"><strong>Why is Cohort Analysis Important for App Marketers?<\/strong><\/h2>\n<p data-path-to-node=\"18\">Without cohort analysis, app metrics can be deceiving. A sudden spike in total active users might look like success, but it could simply be masking a high churn rate among your older users. Here is why cohort analysis is crucial:<\/p>\n<ul data-path-to-node=\"19\">\n<li>\n<p data-path-to-node=\"19,0,0\"><b data-path-to-node=\"19,0,0\" data-index-in-node=\"0\">Optimizing User Acquisition (UA) &amp; ROAS:<\/b> Not all users are created equal. By grouping users by the campaign that acquired them, you can identify which channels bring in high-value users who make purchases, and which channels bring in users who churn after one day. This allows you to reallocate your ad spend to maximize Return on Ad Spend (ROAS).<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"19,1,0\"><b data-path-to-node=\"19,1,0\" data-index-in-node=\"0\">Improving User Retention &amp; Fighting Churn:<\/b> By viewing a cohort retention table, you can pinpoint the exact day users tend to drop off (e.g., a massive drop on Day 3). You can then set up automated re-engagement campaigns (like push notifications) right before the predicted drop-off point.<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"19,2,0\"><b data-path-to-node=\"19,2,0\" data-index-in-node=\"0\">A\/B Testing Product Changes:<\/b> If you introduce a new feature or change your onboarding flow, you can create a cohort of users who experience the new version and compare their lifetime value (LTV) and retention to a cohort using the old version.<\/p>\n<\/li>\n<\/ul>\n<h2 data-path-to-node=\"20\"><strong>Key Metrics to Track by Cohort<\/strong><\/h2>\n<p data-path-to-node=\"21\">When analyzing cohorts in your MMP, focus on these critical KPIs:<\/p>\n<ul data-path-to-node=\"22\">\n<li>\n<p data-path-to-node=\"22,0,0\"><b data-path-to-node=\"22,0,0\" data-index-in-node=\"0\">Retention Rate:<\/b> The percentage of users from a cohort who return to the app on a specific day (e.g., Day 1, Day 7, Day 30).<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"22,1,0\"><b data-path-to-node=\"22,1,0\" data-index-in-node=\"0\">Lifetime Value (LTV):<\/b> The total projected revenue a specific cohort will generate during their entire lifespan in the app.<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"22,2,0\"><b data-path-to-node=\"22,2,0\" data-index-in-node=\"0\">Average Revenue Per User (ARPU):<\/b> The average revenue generated by the users within a given cohort.<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"22,3,0\"><b data-path-to-node=\"22,3,0\" data-index-in-node=\"0\">Cost Per Acquisition (CPA):<\/b> The cost required to acquire the users in that specific cohort, which helps calculate your true ROAS.<\/p>\n<\/li>\n<\/ul>\n<h2 data-path-to-node=\"23\"><strong>Leveraging Cohort Analysis with Affise MMP<\/strong><\/h2>\n<p data-path-to-node=\"24\"><a href=\"https:\/\/affisemmp.com\/\"><b data-path-to-node=\"24\" data-index-in-node=\"0\">Affise MMP<\/b><\/a> provides next-generation cohort analysis designed for apps looking to scale rapidly and profitably. With Affise, you aren&#8217;t just looking at past data; you are predicting future revenue.<\/p>\n<p data-path-to-node=\"25\">Key Affise MMP cohort features include:<\/p>\n<ul data-path-to-node=\"26\">\n<li>\n<p data-path-to-node=\"26,0,0\"><b data-path-to-node=\"26,0,0\" data-index-in-node=\"0\">Granular Data Slicing:<\/b> Break down cohorts by network, campaign, ad creative, geo, or specific in-app events to find your most profitable segments.<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"26,1,0\"><b data-path-to-node=\"26,1,0\" data-index-in-node=\"0\">LTV Forecasting:<\/b> Use advanced predictive models to forecast the Lifetime Value of a cohort within days of acquisition, allowing you to optimize campaigns long before the actual revenue is realized.<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"26,2,0\"><b data-path-to-node=\"26,2,0\" data-index-in-node=\"0\">Unified Cost &amp; Revenue Aggregation:<\/b> Affise MMP pulls together your ad spend and ad revenue, giving you a true, unobstructed view of your cohort ROAS in one centralized dashboard.<\/p>\n<\/li>\n<li>\n<p data-path-to-node=\"26,3,0\"><b data-path-to-node=\"26,3,0\" data-index-in-node=\"0\">Proactive Optimizations:<\/b> Identify underperforming cohorts in real-time and shift your budgets immediately to ensure maximum ROI.<\/p>\n<\/li>\n<\/ul>\n<p data-path-to-node=\"27\">By utilizing the cohort analysis capabilities within Affise MMP, mobile marketers can stop guessing and start making data-driven decisions that foster long-term app growth.<\/p>\n","protected":false},"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false},"class_list":["post-58484","glossary-term","type-glossary-term","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Cohort Analysis Definition: Marketing Glossary | Affise<\/title>\n<meta name=\"description\" content=\"What is Cohort Analysis? 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