Retention curve
reh-TEN-shun kurv
A chart showing what percentage of users continue using a product over time, revealing whether the product has lasting value.
A retention curve plots the percentage of users who return to your product over time. Day 1 is 100% (they all signed up). Day 7 might be 40%. Day 30 might be 20%. Day 90 might be 15%. The shape of the curve tells you whether your product has lasting value.
The critical question is whether the curve flattens or goes to zero. A curve that flattens means a cohort of users finds lasting value and keeps coming back. A curve that declines to zero means every user eventually leaves. No amount of marketing can fix a product whose retention curve goes to zero.
Retention curves should be analyzed by cohort. Users who signed up in January may behave differently from users who signed up in March (because you improved onboarding). Cohort analysis reveals whether product changes are actually improving retention.
Examples
A product's retention curve flattens at 25%.
After 90 days, 25% of each cohort is still active. This means one in four users finds lasting value. The product has PMF for that segment. The team focuses on understanding what differentiates the retained 25% and getting more users like them.
An onboarding improvement shifts the retention curve.
Before the change, Day 7 retention was 30%. After a new onboarding flow, Day 7 retention jumps to 42%. The entire curve shifts upward. More users are reaching the aha moment that makes them stick.
A team compares retention curves across user segments.
Enterprise users retain at 80% after 90 days. SMB users retain at 15%. The difference is stark. The team investigates: enterprise users have dedicated onboarding support. SMB users are left to figure it out alone.
In practice
Read more on the blog
Frequently asked questions
What is a good retention curve?
A curve that flattens, regardless of the level. A product with 15% long-term retention that is stable has product-market fit for that segment. A product with 50% Day 7 retention that declines to zero has a churn problem. The shape matters more than the initial numbers.
How do you improve a retention curve?
Focus on the first few days. Most users who leave do so early. Improve onboarding to get users to the aha moment faster. Then focus on building habits: notifications, integrations, and features that bring users back regularly.
Related terms
Grouping users by when they signed up and tracking their behavior over time to identify trends and measure the impact of changes.
The moment when a new user experiences the core value of a product for the first time, making them likely to return.
The point where a product satisfies strong market demand, evidenced by organic growth and high user retention.
How frequently users return to a product, typically measured as the DAU/MAU ratio.
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