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Adapty Analytics are a powerful suite of tools for data visualization and analysis. You can use the data to gain valuable insights into your user base, make data-driven decisions, and optimize your app's performance.
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:::tip
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Read the [How Adapty Analytics Works](how-adapty-analytics-works) guide to learn more about how Adapty processes analytics data.
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Read the [How Adapty Analytics Works](how-adapty-analytics-works) guide to learn more about data sources and processing.
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## Overview
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Main article: [Cohort Analysis](analytics-cohorts)
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The Cohorts tab allows you to split users into groups based on the installation date, and analyze their conversion rates.
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The Cohorts tab allows you to split users into groups based on installation date, and analyze their conversion rates.
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Main article: [Funnels](funnels)
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The Funnels tab visualizes your users' journeys — from installing the app to purchasing a subscription, and the following renewals. You can detect the users' drop-off points to optimize your strategy.
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The Funnels tab visualizes the stages of user engagement with your app. You can see which proportion of installations result in subscriptions, and how long the users remain subscribed. Take note of common drop-off points to optimize your strategy.
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Main article: [Conversion](conversion)
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The Conversion tab displays graphs for conversion rates at different stages of the user journey. It helps you analyze a particular transition point, such as from billing issue to renewal.
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The Conversion tab displays graphs for conversion rates at different stages of the user journey. It highlights common user choices during transition points, such as from trial to subscription, or billing issue to successful renewal.
Main article: [Controls](controls-filters-grouping-compare-proceeds)
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Adapty Analytics include filters and grouping controls to simplify behavior analysis for specific audiences. For example, you can filter the retention graph by store and compare user behavior between Android and iOS.
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You can use filters and grouping controls to view data pertaining to a specific subsection of users. For example, you can filter the retention graph by store and compare user behavior between Android and iOS.
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