Churn risk patterns

Churn risk patterns help identify users who might stop using your product. The most reliable warning signs are simple changes in behavior: users log in less often, spend less time in the product, or stop using their regular features. Think of it like a gym membership — someone who usually goes 3 times a week starting to show up only once a week might be close to canceling.

Early warning signs usually appear in a predictable order. First, users start skipping their regular usage times. Then they log in less frequently. Finally, when they do log in, they do less with the product. By watching for these basic changes in behavior, teams can reach out to users before they completely stop using the product.^[1]

Some changes in usage are normal and don't indicate real risk. For example, many products see less usage during holidays or certain business seasons. The key is to identify unusual drops in individual user activity compared to their normal patterns.