Been digging into our churn data lately. Surprising how much we can learn about why users leave.
Noticed some patterns around feature usage and engagement drops before churning.
Anyone else found key indicators that predict churn? Curious what metrics you track.
Engagement decay is a big red flag. Look for users who gradually do less over time.
We track the number of core actions per week. If it steadily declines over 3-4 weeks, that user is likely to churn soon.
Also, pay attention to login patterns. Users who switch from daily logins to sporadic use often leave within a month.
One counterintuitive finding: users who blast through all features quickly tend to churn fast. They get bored. Slower, steady engagement usually means better retention.
Bottom line: sudden behavior changes and gradual declines are your main churn indicators. Act on those trends fast.
Login frequency dropped hard for us. Fewer logins fewer actions churn soon after. Watch those numbers closely.
Session frequency and early feature adoption are solid indicators. I’d add payment patterns for paid apps.
Users who suddenly stop making in-app purchases or downgrade subscriptions often churn soon after. Tracking spending trends helps spot at-risk users before they leave.
Also, look at support ticket volume. A spike in complaints or questions can signal frustration that leads to churn.
Yeah, churn data is a goldmine. One of our biggest wins was tracking session frequency.
We saw users who dropped from 5+ weekly sessions to 2-3 were way more likely to churn within 30 days. Let us get ahead of it with targeted re-engagement campaigns.
Also, feature adoption in the first week was huge. Users who didn’t try at least 3 core features rarely stuck around long-term.
Surprisingly, time in app wasn’t as predictive as we thought. Some power users churned despite long sessions. Turned out they were hitting friction points we hadn’t noticed.
My advice? Look for sudden changes in behavior patterns. They often signal upcoming churn better than static metrics.
Time in app can be misleading. We saw users with long sessions churn too. Watch for drops in key actions instead of just total time spent.