> ## 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.

# How to Track and Improve User Retention

> Measure Day 7, 30, and 90 retention rates for your crypto app with cohort analysis, identify churn patterns, and build segments to re-engage at-risk users.

Acquiring users is expensive. Keeping them is where the real growth happens. In crypto, a 10 percent improvement in Day 7 retention can be worth thousands in LTV. This guide shows you how to measure retention, spot churn, and re-engage at-risk users.

## Part 1: View Retention on the Overview Page

The fastest way to see retention is on your **Overview** dashboard:

<Steps>
  <Step>
    Open the **Overview** page in Formo.
  </Step>

  <Step>
    Scroll down to the **Retention** section. You'll see:

    * **Day 7 Retention**: Percent of users active on Day 7 (default 14-day window)
    * **Day 30 Retention**: Percent of users active on Day 30
    * **Day 90 Retention**: Percent of users active on Day 90
    * **Delta**: Week-over-week change (up or down)
  </Step>

  <Step>
    Compare your retention to your baseline. A 2-3 percent week-over-week improvement is excellent. A 5+ percent drop is a red flag.
  </Step>
</Steps>

<Frame caption="Retention metrics on the Overview page">
  <img src="https://mintcdn.com/formo/N-uk5SnfJVeheQMa/images/screenshots/overview.png?fit=max&auto=format&n=N-uk5SnfJVeheQMa&q=85&s=8a871273af3f585309870f6b04db478a" alt="Overview retention" width="1153" height="673" data-path="images/screenshots/overview.png" />
</Frame>

## Part 2: Build a Retention Cohort Chart

For deeper insights, create a retention cohort chart on a dashboard. This shows how each cohort of users (grouped by signup date) retains over time:

<Steps>
  <Step>
    Click **Dashboards** → **Create Chart** → select **Retention** chart type.
  </Step>

  <Step>
    Choose your **cohort grouping**:

    * **Daily**: See retention of users who signed up on each day
    * **Weekly**: Group by signup week (cleaner view for smaller apps)
    * **Monthly**: For apps with high volume
  </Step>

  <Step>
    Click **Save to Dashboard**. This cohort chart is now live.
  </Step>
</Steps>

The retention table shows cohorts (rows) and retention days (columns). Green cells mean high retention. Red means churn. Look for diagonal patterns:

* **Declining diagonal**: Older cohorts have worse retention. (Possible: product degraded, new cohorts are higher quality)
* **Level diagonal**: Consistent retention across all cohorts. (Healthy.)
* **Rising diagonal**: Newer cohorts retain better. (Possible: product improvements are working)

<Frame caption="Retention cohort table showing Day 7, 30, 90">
  <img src="https://mintcdn.com/formo/58iudW1HQTF0XT4k/images/retention.png?fit=max&auto=format&n=58iudW1HQTF0XT4k&q=85&s=e343c2c6c650ae57a5945cfd297da485" alt="Retention table" width="2314" height="1310" data-path="images/retention.png" />
</Frame>

## Part 3: Identify Churn Patterns

The **Insights** page uses AI to spot churn signals. Check it weekly:

<Steps>
  <Step>
    Click **Insights** in the sidebar.
  </Step>

  <Step>
    Look for the **Issues** section. Formo flags patterns like:

    * "Users from country=US are churning 25% faster than average"
    * "Mobile users have 40% lower Day 7 retention"
    * "Cohort from Week 3 of March dropped 15% on Day 5"
  </Step>

  <Step>
    Click on an insight to drill into the data. Ask: Is this a real problem or noise?
  </Step>
</Steps>

**Red flags to act on immediately:**

* A sudden drop in Day 7 retention (5%+ week-over-week) usually means a bug or product issue
* A specific geography or device churning faster suggests a UX or localization problem
* A cohort that performs poorly across all retention windows suggests they were bad-fit users to begin with

## Part 4: Segment Churned and At-Risk Users

To re-engage users, you must first identify them. Use the **Users** page to create segments:

<Steps>
  <Step>
    Click **Users** in the sidebar to see all users.
  </Step>

  <Step>
    Apply filters to find at-risk users:

    * **Lifecycle = "Churned"**: Users inactive for 30+ days
    * **Lifecycle = "Resurrecting"**: Users who returned after being inactive
    * **Last Activity \< 7 days ago**: Users who haven't returned this week
  </Step>

  <Step>
    Click **Save as Segment**. Name it "Churned Users Q1 2026".
  </Step>

  <Step>
    Once saved, you can export this segment as CSV for re-engagement campaigns or use it to build exclusion lists.
  </Step>
</Steps>

<Frame caption="User lifecycle stages in the Users page">
  <img src="https://mintcdn.com/formo/Qbe3dL6juMIXAS6y/images/users.png?fit=max&auto=format&n=Qbe3dL6juMIXAS6y&q=85&s=15e1905c31cbe5523c4b7216a738a0b3" alt="Users page" width="2282" height="926" data-path="images/users.png" />
</Frame>

<Note>
  **User Lifecycle Stages:** New, Returning, Power User, Resurrected, At Risk, and Churned, assigned from each wallet's activity recency and frequency. See [User Lifecycle](/features/wallet-intelligence/wallet-profiles#user-lifecycle) for the exact rules and thresholds.

  Use these stages to build segments for targeted campaigns.
</Note>

## Part 5: Export Your Segment for Re-Engagement

<Steps>
  <Step>
    In your saved segment, click **Export as CSV**.
  </Step>

  <Step>
    Download the file. It contains wallet addresses, ENS names, and event counts.
  </Step>

  <Step>
    Use this list to:

    * Send a Farcaster DM campaign: "We missed you. Here's what's new."
    * Create a rewards campaign: "Return this week, get 100 points."
    * Build a lookalike audience: "Find more users like these high-retainers."
  </Step>
</Steps>

## Part 6: Set Up Alerts for Key User Events

Monitor important user activity with alerts. Get notified when high-value wallets connect or key events happen:

<Steps>
  <Step>
    Go to **Project Settings → Alerts**.
  </Step>

  <Step>
    Click **Create Alert**.
  </Step>

  <Step>
    Configure your alert trigger (e.g., whale wallet connects, transaction from a high-value user). Choose notification method (Slack webhook).
  </Step>

  <Step>
    Save. You'll be alerted in real time when the event fires.
  </Step>
</Steps>

See [Alerts documentation](/features/product-analytics/alerts) for full setup.

## Part 7: Use Ask Formo to Understand Churn

Open **Ask Formo** (the AI assistant) and ask natural language questions:

* "Why is Day 7 retention down 10% this week?"
* "Which countries have the worst retention?"
* "Do mobile users churn faster than web?"
* "What do my highest-retaining users have in common?"

Formo analyzes your data and provides insights with supporting numbers.

<Frame caption="Ask Formo interface for analytical questions">
  <img src="https://mintcdn.com/formo/5S3MPZWP8GYgbzVs/images/ai.png?fit=max&auto=format&n=5S3MPZWP8GYgbzVs&q=85&s=c50d8476296fc92e85607f7651c5858d" alt="Ask Formo" width="963" height="441" data-path="images/ai.png" />
</Frame>

## Real-World Example: Improving Retention by 5%

**Scenario**: Your DEX app has 25% Day 7 retention. You want to hit 30%.

<Steps>
  <Step>
    **Identify the problem** (Week 1): Create a retention cohort chart. See that mobile users churn 15 points faster than web.
  </Step>

  <Step>
    **Understand the why** (Week 2): Use Ask Formo: "Why are mobile users churning faster?" Discover: mobile users have 3x higher transaction failures due to MetaMask timeout.
  </Step>

  <Step>
    **Build a fix** (Week 3): Increase timeout from 30s to 60s. Roll out to 10% of mobile users.
  </Step>

  <Step>
    **Measure impact** (Week 4): Create a segment of "mobile users who upgraded on Day 3". Compare their Day 7 retention vs old cohorts. See 8% improvement in that segment.
  </Step>

  <Step>
    **Roll out fully** (Week 5): Deploy 60s timeout to all. Your Day 7 retention climbs from 25% to 28%. Repeat for other friction points.
  </Step>
</Steps>

By the end of 6 weeks, you've hit 30% Day 7 retention. That's a 20% improvement in user value.

## Best Practices

* **Weekly deep dives**: Check Insights every Monday. Act on red flags immediately.
* **Cohort comparisons**: Compare Week 1 vs Week 2 cohorts. Which is healthier? Why?
* **Segment tests**: Create two segments (e.g., "High fee payers" vs "Low fee payers"). Compare retention. High spenders often retain better, revealing your value lever.
* **Pair with conversion**: High conversion doesn't mean high retention. A user who swaps once and never returns is not a retained user. Optimize for both.
* **Monitor by source**: Create segments by referrer. Which traffic sources give best-retaining users? Double down there.
* **Check wallet labels**: If you use [Wallet Intelligence](/features/wallet-intelligence/overview), segment by wallet label (e.g., "Verified Coinbase User"). Some labels correlate with higher retention.

## Churn Prevention Playbook

Churn isn't just "users who left." It's a measurable, predictable pattern. Use this playbook to define, detect, and prevent churn in your specific app.

**Churn Definition by App Type**

| App Type            | Churn Threshold | Rationale                                                             |
| ------------------- | --------------- | --------------------------------------------------------------------- |
| DeFi (DEX, Lending) | 30+ days        | Long gaps between trades are normal, but 30 days suggests abandonment |
| Gaming              | 14+ days        | Daily drivers; 2 weeks without a session signals churn                |
| Bridge/Cross-chain  | 60+ days        | Multi-week cycles are normal; 60 days is the safety threshold         |

**Monthly Churn Rate Query**

Use this SQL to calculate month-over-month churn:

```sql theme={null}
SELECT
  toStartOfMonth(first_seen) as cohort_month,
  count(*) as total_users,
  countIf(last_seen < now() - INTERVAL 30 DAY) as churned_users,
  round(countIf(last_seen < now() - INTERVAL 30 DAY) / count(*) * 100, 2) as churn_rate_pct
FROM users
GROUP BY cohort_month
ORDER BY cohort_month DESC
```

**At-Risk Segments to Build**

<Note>
  Create these three segments in the Users page and save them for weekly monitoring:
</Note>

1. **At-Risk Power Users** (High priority)
   * Filter: `Sessions > 20` AND `Last Activity 7-14 days ago`
   * Why: These users have proven value. Re-engage before they churn.

2. **New Users Not Returning** (Medium priority)
   * Filter: `Sessions < 5` AND `Last Activity 3-7 days ago`
   * Why: Early-stage friction. A small push converts them to returning users.

3. **Declining Activity** (Watch list)
   * Filter: `Sessions > 10` AND `Last Activity 7-30 days ago`
   * Why: Gradual drop-off. These need incentives before hitting 30+ days.

**Churn Alert Templates**

Set up these alerts in Project Settings:

* **Whale Going Inactive**: User with `Lifetime Value > $10k` AND `Last Activity > 7 days`
* **Power User Declining**: User with `Sessions > 15` AND `Day-over-day activity drop > 50%`
* **Failed Transaction Spike**: Cohort-level alert if `Failed Transactions` increase 3x week-over-week

**Re-engagement Campaign Strategies**

| Segment                 | Trigger                       | Action                         | Expected Lift |
| ----------------------- | ----------------------------- | ------------------------------ | ------------- |
| Power users going quiet | 7 days of inactivity          | VIP email + bonus points       | 15-25% return |
| New users stalling      | 3 days, fewer than 5 sessions | In-app nudge + tutorial replay | 20-30% return |
| Recently churned        | 30-45 days inactive           | "We miss you" discount offer   | 10-15% return |

**Analyze Churned User Behavior with Flows**

Use [User Path charts](/guides/flows) to understand what churned users did in their last session:

1. Go to **Dashboards** > **Create Chart** > select **User Path**
2. Filter by users whose lifecycle is **Churned**
3. Look for patterns: failed transactions, abandoned flows, or limited exploration

Compare churned vs. retained users side by side:

* **Churned cohort**: Active 60+ days ago, has not returned in 30+ days
* **Retained cohort**: Active 60+ days ago, has returned in the last 30 days

Compare their first-week behavior: sessions count, features used, transaction volume, and entry referrer. This reveals what retained users do differently - and what to optimize in onboarding.

## Next Steps

You've set up retention tracking. Here's what to do next:

* **[Create a Conversion Funnel](/guides/funnels)**: High retention is good, but you need high conversion first.
* **[Use Segments for Re-engagement](/features/wallet-intelligence/segments)**: Build audiences of churned users for campaigns.
* **[Build a Custom Dashboard](/guides/custom-dashboard)**: Track retention alongside other key metrics in one view.
* **[Set Up Alerts](/features/product-analytics/alerts)**: Get notified when high-value users or key events happen.
* **[Explore Your Users](/features/wallet-intelligence/wallet-profiles)**: Click on a user in the Users page to see their full profile, including lifecycle stage and activity feed.

## FAQ

<AccordionGroup>
  <Accordion title="How is retention calculated?">
    Day 7 retention = (Users active on Day 7 / Users who signed up on Day 0) \* 100

    A user is considered active if they have at least one session (page view or transaction) on that day.

    Example: 1000 users sign up on Monday. 250 of them return and are active on the following Monday. Day 7 retention = 25%.
  </Accordion>

  <Accordion title="What's the difference between Day 7, 30, and 90 retention?">
    * **Day 7**: Users who returned within 7 days of signup. Measures short-term activation.
    * **Day 30**: Users active within 30 days. Measures habit formation.
    * **Day 90**: Users active within 90 days. Measures long-term value.

    All three matter. Day 7 catches immediate churn. Day 30 shows if you built a habit. Day 90 shows if users stick around.
  </Accordion>

  <Accordion title="What user lifecycle stage should I re-engage first?">
    Priority order:

    1. **Resurrecting**: Users who just came back. Momentum is on your side.
    2. **At-risk Returning**: Users with only 2-3 sessions. Easy to convert to Power Users.
    3. **Recent Churned**: Users inactive for 30-60 days. Still remember your product.
    4. **Old Churned**: Users inactive for 6+ months. Hard to re-activate.

    Focus on 1 and 2 first for best ROI.
  </Accordion>

  <Accordion title="Can I compare retention across different UTM sources?">
    Yes. Create two retention charts (or use breakdowns). Filter the first by UTM Source = "twitter" and the second by UTM Source = "discord". Compare Day 7 retention across both. You'll likely see significant differences.

    If one source has 2x better retention, invest more in that channel.
  </Accordion>

  <Accordion title="Can I set a custom retention window?">
    By default, retention is measured from signup date. You can create custom cohort charts by setting a custom event (e.g., "first\_transaction") as your cohort start. Contact support if you need help.
  </Accordion>
</AccordionGroup>