Been diving deep into customer analytics trying to get ahead of churn before it happens.
Tested a bunch of different metrics but curious what’s actually moved the needle for others. Support ticket volume seems obvious but wondering if there are less obvious signals that work better.
Feature usage depth beats frequency for me. Users who stop going past the second screen usually churn within 2 weeks.
Also watch for support ticket sentiment, not just volume. Someone asking “how do I delete my account” hits different than “feature not working”.
Push notification open rates dropping below 8% was our strongest signal. Way better predictor than login frequency in our tests.
In-app behavior changes work better than activity metrics for me.
When users stop customizing settings or skip onboarding steps they used to complete, that usually means they are checking out mentally.
Also track how they respond to prompts inside the app. People who start ignoring upgrade suggestions or dismiss helpful tips are often one foot out the door already.
Session duration matters more than most people think. When users start rushing through stuff they usually bail soon.
Time between logins drops fast before people leave.
Payment method failures and declined transactions are key warning signs. Users facing billing issues and not updating payment info within 48 hours tend to have an 80% churn rate. Also monitor negative actions like removing integrations, downgrading plans, or deleting data. These indicate intent to leave. Many overlook these signals as they focus on usage patterns instead.