Feature · Retention
Retention: who comes back?
See who returns after signup, a first purchase or any key action. Cohort-based retention that shows real stickiness, not vanity numbers.
- Cohort-based retention
- Any start and return event
- Day, week or month view
| Cohort | W0 | W1 | W2 | W3 | W4 | W5 | W6 | W7 |
|---|---|---|---|---|---|---|---|---|
| Sep 1 | 100% | 58% | 46% | 41% | 38% | 36% | 35% | 34% |
| Sep 8 | 100% | 61% | 49% | 43% | 40% | 38% | 37% | |
| Sep 15 | 100% | 55% | 44% | 40% | 37% | 36% | ||
| Sep 22 | 100% | 63% | 52% | 47% | 44% | |||
| Sep 29 | 100% | 66% | 54% | 49% |
The basics
What retention means
Retention is the share of people who come back after doing something once. It answers: of the people who did X in a given week, how many did Y later?
Traffic and signups can look great while the product fails to stick. Retention tells you what those numbers can't:
- Whether people build a habit: do they return after the first visit?
- When they leave: after day 1, week 1 or month 1?
- Which groups stick: do people from one source or on one plan return more often?
In Pieowl, retention is built on your events. You choose a start event (for example signup_completed) and a return event (for example project_opened). Pieowl groups people by when they first did the start event and shows what share did the return event in each period after.
You can count people who were active in a given period, or in or after it. You can also limit the chart to a saved cohort or to people with a certain property. The same events power funnels, profiles and the MCP server, so there's nothing extra to track.
Retention on every plan
What you can do with retention
From weekly cohorts to group comparisons, retention gives you the stickiness signal.
Cohort-based retention
Group people by when they first did the start event. See what share return in period 1, 2, 3 and beyond.
Any start and return event
Define retention your way: signup → login, first purchase → repeat purchase, feature used → feature used again.
Day, week or month
Switch the period to match how often people should use your product. A daily app and a monthly tool need different views.
Filter by property or cohort
Limit the chart to people from one source, on one plan, or in a saved cohort. Compare groups to see who sticks.
Read the grid at a glance
Cohorts are rows and periods are columns. High numbers mean people stay; a sharp drop shows where to look.
Dashboards and sharing
Add retention charts to a dashboard next to funnels and other reports. Share a chart by link, with an optional password.
Set up
How to read a retention chart
Retention charts are simple once you know what to look for.
- 1
Pick your start and return events
The start event defines the cohort, for example signup_completed. The return event defines "came back", for example a page view or feature_used.
- 2
Read the grid
Rows are cohorts, such as everyone who signed up in one week. Columns are periods after that. Each cell is the share of the cohort that came back in that period.
- 3
Spot patterns
Look for cohorts that hold up and cohorts that drop fast. Filter by source, plan or cohort to see which people stick, and focus your work there.
Use cases
How teams use retention
Founders and product teams use retention to separate signal from noise.
Product teams
See which features and flows lead to repeat use. Put work into what keeps people, not only into signups.
Founders
Retention is one of the clearest signs that people need your product. A week-4 retention number often says more than top-line growth.
Growth and marketing
Check whether onboarding changes improve retention. Compare sources and campaigns by how many of their users come back.
FAQ
Frequently asked questions
Common questions about retention analytics with Pieowl.
What's the difference between retention and funnel analysis?
Funnels answer "where do people drop off in a sequence?" Retention answers "of the people who did X, how many came back to do Y?" Both use the same events. Retention looks at repeat behavior over time; funnels look at one flow.
Can I use any events for retention?
Yes. You choose a start event, such as signup_completed or first_purchase, and a return event, such as a page view or feature_used. Pieowl groups people by when they did the start event and shows what share did the return event later.
Does retention work without cookies?
Yes, with one thing to know. Visitor IDs change every day for people you haven't identified, so long-term retention is most accurate for people you identify, for example after login. Call identify and their visits link to one profile across days.
How do I know if my retention is good?
There's no universal benchmark. It depends on your product and audience. What matters is the trend and the comparison between groups: is it improving, and which groups stay longest?
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