Been digging into our retention data lately. Seeing some interesting correlations between user engagement patterns and subscription renewals.
Curious how others are using retention metrics to predict and influence long-term user behavior. What key indicators are you tracking?
Churn rate tells us everything Low churn users buy more stuff
We look at daily active users mostly. It’s a simple metric but it tells us a lot. When DAU goes up, subscriptions usually follow.
Retention rate is key for me. I track how many users come back after 1, 7, and 30 days. Higher retention usually means more subscriptions and revenue. I’ve found improving the first-time user experience has the biggest impact. Onboarding tutorials and welcome emails that highlight core features seem to keep people coming back more often.
Forget vanity metrics. Focus on activation rate within the first 3 days. It’s the best predictor of long-term retention and subscription growth I’ve seen.
Track how many users complete your core action - whether that’s making a post, finishing a lesson, or whatever defines ‘active’ for your app.
If you can boost that number, everything else improves. Higher activation means more engaged users, lower churn, and better word-of-mouth growth.
We increased our 3-day activation from 22% to 38% by simplifying onboarding and sending targeted push notifications. Saw a 31% jump in 60-day retention as a result.
Retention’s been huge for us. We track a bunch, but these two have been game-changers:
Feature adoption rate in the first week. Users who engage with 3+ core features tend to stick around longer and upgrade more.
Time between sessions. As it shrinks, renewal rates climb. We started sending ‘quick win’ push notifications to bring people back faster.
Also, cohort analysis was eye-opening. Saw that users from Facebook ads churned way faster than organic. Helped us rethink our ad spend.
These metrics guide our product roadmap now. We’re always asking: ‘Will this feature boost early adoption or session frequency?’