Been analyzing retention metrics lately and it seems like we’re overlooking some critical insights.
Cohort analysis looks good, but user behavior could have more layers that we’re not seeing.
How do you explore retention patterns more thoroughly?
Track how users interact with key features instead of just focusing on login dates. Users who engage with core features in the first week tend to stay longer. Also, monitor session duration. High retention rates can mask users who open the app without taking action.
Don’t just track retention by time - break it down by what users actually do. Compare people who finished onboarding vs those who bailed. See how users who hit your paywall perform against free users. Credit card users tend to stick around way longer than other payment methods. The magic happens when you can pinpoint exactly where users drop off in their journey.
I track what users do right after hitting key milestones. Most people just check “did they come back” but I dig deeper - what did they actually do when they returned?
For example, I separate users who return but stay stuck on the home screen from those who jump into main features. Same retention numbers, completely different engagement quality.
I’ve changed how I look at retention windows. Instead of the standard day 1, 7, 30 approach, I track retention after specific actions. Users who complete their first transaction behave totally differently than browsers.
Biggest revelation? Some of my “high retention” users were just opening the app out of habit without getting real value. Now I measure meaningful actions, not just app opens.
Different traffic sources can show different behaviors. It can be helpful to segment users that way.
Look at what users do just before leaving.