Growth, activation and activity hours
Weekly growth accounting, stickiness, activation, activity hours, behaviour by app version, event properties and launch impact in Cockpitify.
These screens go beyond daily actives: is the app growing, do people come back, which first steps matter, and what changed after a release. They need usage analytics.
Open them
- Phone: on the Summary tab, tap the Growth row, or Depth under the links.
- On the web: Feature usage, then Growth or Depth at the top. The Summary page also shows a growth line on every plan.
Growth
- Weekly lifecycle: each week’s new, retained and came back people stacked up, and those gone below the line. On Pro you can show premium and free apart.
- Growth ratio: (new + came back) ÷ gone over the last 4 weeks. Above 1 the app is growing; below 1 it’s shrinking.
- Stickiness: DAU/MAU for a daily habit, WAU/MAU for a weekly one.
- Days active in the last 28: how many people came on 1, 2–3, 4–7, 8–14, 15–21 or 22–28 days. Tap a bar to see who.
Activation
Pick an event that stands for the moment people see the value (for example finishing their first quiz) and a window of 1 or 7 days. Of the people first seen 28–89 days ago, Cockpitify shows how many did it, and how those people and the rest compare on week-4 return and paying within 28 days. It’s a relation, not a cause.
Activity hours
A weekday × hour heat map of average active people over 4 weeks, in your report time zone. Time notifications and campaigns for the darkest cells.
Behaviour by version
For each app version: people, premium share, AI cost per person and day-7 return, plus the share of people not on the newest version. Crash-free rates are on Release health.
Event properties
Break an event down by the values of one of its properties, for example level on quiz_done: uses and people per value. Only keys you allow are broken down, so personal data never shows; add keys under Allowed keys on the web (at most 20). Values come from the raw events (14 days by default).
Launch impact
Pick a date, or a version’s first day, and compare the 15 days before with the days after: new people, active people, new payers, subscriptions ended and AI cost, as daily averages. It doesn’t separate seasons or campaigns.