> ## Documentation Index > Fetch the complete documentation index at: https://docs.formo.so/llms.txt > Use this file to discover all available pages before exploring further. # Retention > Measure user retention with cohort analysis to identify which user groups return over time, track stickiness, and spot churn patterns in your onchain app. Measure the stickiness of your product with different cohorts of users. Understanding user retention and engagement allows you to identify which user cohorts are more likely to take specific actions within a given time period. You can select which event to use to calculate week-on-week user retention. This gives product teams better insight on retention rates for specific features and user flows. For example, measure retention based on: * Transaction completions * Feature usage * Wallet connections * [Custom events](/features/product-analytics/custom-events) specific to your app *** ## How to analyze user retention Retention analysis shows how many users come back to your app over time. This guide walks you through reading retention charts and improving user stickiness. ### What is a cohort retention chart? A cohort is a group of users who started using your app in the same time period (e.g., users who first connected in Week 1). Retention tracks what percentage of each cohort returns in subsequent weeks. | Week 0 | Week 1 | Week 2 | Week 3 | Week 4 | | ------ | ------ | ------ | ------ | ------ | | 100% | 40% | 25% | 20% | 18% | This example shows: of users who started in Week 0, 40% returned in Week 1, 25% in Week 2, etc. ### Step 1: Create a Retention chart Retention is a chart type you add to a dashboard (board), not a separate nav page. 1. Go to the [Formo Dashboard](https://app.formo.so) 2. Select your project 3. Open **Dashboards** in the left navigation, then open or create a board 4. Click **Add Chart** and choose the **Retention** chart type ### Step 2: Choose the retention event Select which event defines "active" for retention tracking: | Event | What it measures | | ---------------- | -------------------------------------- | | **connect** | Users who connected their wallet again | | **transaction** | Users who transacted again | | **page** | Users who visited any page | | **Custom event** | Users who performed a specific action | For crypto apps, `transaction` retention is usually the most meaningful metric because it shows who's actually using your protocol. ### Step 3: Read the retention matrix The retention chart displays: * **Rows**: Cohorts (grouped by start week/month) * **Columns**: Time periods after start * **Cells**: Percentage of cohort still active Retention Chart **Color coding:** * 🟢 Green = above average retention * 🟡 Yellow = average retention * 🔴 Red = below average retention ### Step 4: Identify patterns **Healthy retention curve:** * Sharp drop in Week 1 (normal) * Gradual stabilization by Week 3-4 * Flat line after stabilization (loyal users) **Concerning patterns:** * Continuous decline without stabilization * Large drop-offs in later weeks * Significant variance between cohorts ### Step 5: Compare cohorts Look for cohorts with better or worse retention: **Questions to ask:** * Did a product change improve retention for newer cohorts? * Do users from certain campaigns retain better? * Is there seasonal variation in retention? ### Retention benchmarks for crypto apps | App Type | Week 1 | Week 4 | Week 8 | | -------- | ------ | ------ | ------ | | DEX | 30-40% | 15-25% | 10-20% | | Lending | 25-35% | 15-20% | 10-15% | | Gaming | 35-50% | 20-30% | 15-25% | ### Improving retention Based on your retention analysis: **If Week 1 drop-off is too high:** * Improve onboarding experience * Send follow-up notifications * Add incentives for early engagement **If long-term retention is declining:** * Add new features or content * Implement re-engagement campaigns * Analyze churned users for common patterns **If certain cohorts retain better:** * Identify what made them different * Replicate successful acquisition channels * Apply learnings to current users ### Using retention with other features | Feature | How to combine | | ------------------- | --------------------------------------------- | | **Segments** | Create segments of retained vs. churned users | | **Funnels** | Measure conversion for retained users | | **Alerts** | Get notified when retention drops | | **Wallet Profiles** | Investigate high-retention users | ### Next Steps Create segments based on retention behavior Track daily active users Investigate churned users Analyze conversion for retained users