Find the habit that makes users come back.
Retention Curves show what share of each cohort returns in week 1, 2, 4 and beyond, and which features the returning users had in common.
Cohorts by sign-up date, or any first action
Group users by when they signed up, first ordered, or first used a feature. Choose what counts as coming back: any visit, or a meaningful action like a second order.
- Day, week or month views with rolling or fixed windows.
- Unbounded retention for products people use irregularly.
| Cohort | M0 | M1 | M2 | M3 | M4 |
|---|---|---|---|---|---|
| Jan | 100% | 42% | 33% | 29% | 27% |
| Feb | 100% | 45% | 35% | 31% | 28% |
| Mar | 100% | 51% | 41% | 36% | 34% |
| Apr | 100% | 54% | 44% | 39% | |
| May | 100% | 57% | 47% |
Split curves by the features people used
Compare users who tried a feature in their first week with those who didn't. The gap between the curves shows which habits are worth pushing new users toward.
- Correlation, clearly labeled. Zortilla shows the gap and the sample size, and suggests an experiment to prove the cause.
Ask what changed between cohorts
Ask Zortilla compares two cohorts and lists the differences in onboarding steps, features used and acquisition source.
Flexible windows
Daily, weekly or monthly, with custom return events.
Save as cohorts
Any curve becomes a cohort you can target or export.
Habit finder
Ranks the first-week actions most linked to week 4 retention.
You made it to the bottom. Now let's get your users here.
Every page you scrolled past was a step in a funnel. Install Zortilla and see the same picture for your own product, with the reasons people leave at each step.