Skip to main content
The Retention Report helps you understand how well you retain users over time. It uses cohort analysis to show what percentage of users return to your site after their first visit.

​
What is a Retention Report?

Retention analysis tracks groups of users (cohorts) based on when they first visited your site, and measures how many return on subsequent days. This helps you:
  • Measure the stickiness of your product or content
  • Identify trends in user engagement
  • Evaluate the impact of product changes on retention
  • Understand your most loyal user segments

​
Key Concepts

Cohort

A group of users who first visited on the same date

Cohort Date

The date of the user’s first visit to your site

Day Number

Number of days since the cohort date (Day 0, Day 1, Day 2, etc.)

Retention %

Percentage of the cohort that returned on each day

​
How Retention Works

1

Cohort Creation

Users are grouped into cohorts based on the date of their first visit to your website.
2

Track Returns

The system tracks when users from each cohort return to your site on subsequent days.
3

Calculate Percentages

For each cohort and day, calculate what percentage of the original cohort returned.
4

Visualize Trends

Display the data in a retention matrix showing retention rates over time.

​
Reading the Retention Report

The Retention Report displays a matrix where:
  • Rows represent cohorts (grouped by first visit date)
  • Columns represent days since first visit (Day 0 through Day 31)
  • Values show the percentage of users who returned

​
Example Interpretation

Cohort Date | Day 0 | Day 1 | Day 7 | Day 14 | Day 30
------------|-------|-------|-------|--------|--------
2024-01-01  | 100%  | 25%   | 15%   | 10%    | 8%
2024-01-02  | 100%  | 30%   | 18%   | 12%    | 9%
2024-01-03  | 100%  | 28%   | 20%   | 15%    | 11%
Insights from this example:
  • Day 0 is always 100% (the cohort’s first visit)
  • 25-30% of users return the next day (Day 1)
  • By Day 30, 8-11% of users are still active
  • The January 3rd cohort shows better retention, suggesting something improved

​
Use Cases and Insights

​
Measure Product Engagement

Track how engaging your product or content is by measuring how often users return.Questions to answer:
  • What percentage of new users come back the next day?
  • How does retention change over the first week? First month?
  • Are we building a habit with our users?
Healthy retention rates vary by industry. SaaS products often target 40-50% Day 1 retention and 20-30% Day 7 retention.

​
API Usage

curl -X POST https://your-umami-instance.com/api/reports/retention \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "websiteId": "your-website-id",
    "parameters": {
      "startDate": "2024-01-01T00:00:00Z",
      "endDate": "2024-01-31T23:59:59Z",
      "timezone": "America/New_York"
    },
    "filters": {}
  }'

​
Response Format

The API returns retention data with: 
[
  {
    "date": "2024-01-01",
    "day": 0,
    "visitors": 1000,
    "returnVisitors": 1000,
    "percentage": 100
  },
  {
    "date": "2024-01-01",
    "day": 1,
    "visitors": 1000,
    "returnVisitors": 250,
    "percentage": 25
  }
]

​
Analyzing Retention Curves

​
Typical Retention Patterns

After an initial drop, retention stabilizes at a consistent level.
Day 0: 100% → Day 1: 40% → Day 7: 25% → Day 30: 20%
What it means: You have a core group of engaged users. Focus on growing this segment.
Retention continuously declines with no plateau.
Day 0: 100% → Day 1: 30% → Day 7: 10% → Day 30: 2%
What it means: Users aren’t finding long-term value. Focus on improving engagement and onboarding.
Each cohort retains better than previous cohorts.
Cohort A: Day 7: 15%
Cohort B: Day 7: 20%
Cohort C: Day 7: 25%
What it means: Your improvements are working! Keep iterating.
After initial drop, retention actually increases.
Day 0: 100% → Day 1: 40% → Day 7: 35% → Day 30: 45%
What it means: You’re building strong habits. Users who stick around become more engaged over time.

​
Optimization Strategies

Improve Onboarding

A strong first experience drives Day 1 and Day 7 retention. Guide new users to “aha” moments quickly.

Email Campaigns

Re-engage users with targeted emails on Days 1, 3, and 7 to bring them back.

Push Notifications

For mobile apps, push notifications can significantly improve retention when used thoughtfully.

Content Cadence

Publish new content on a consistent schedule to build a habit of returning.
The retention report shows data up to Day 31. For longer-term retention analysis, you may need to export data and analyze it separately.

​
Best Practices

  1. Set retention goals: Define target retention rates for key days (1, 7, 30)
  2. Monitor trends: Look for upward or downward trends in cohort retention
  3. Segment your analysis: Different user types may have different retention patterns
  4. Focus on early retention: Improvements in Day 1-7 retention have the biggest impact
  5. Test and iterate: Run experiments to improve retention and measure the impact
Compare your retention rates to industry benchmarks, but remember that “good” retention varies significantly by product type and business model.

​
Next Steps

User Journeys

Understand what retained users do differently with Journey Reports

Goal Tracking

Track specific actions that correlate with better retention

Build docs developers (and LLMs) love

Get started for freeTalk to us