In short
Churn is when users or customers stop using a product or cancel their subscription. It is usually measured as churn rate: the share of users lost during a set period. High churn means a product loses users faster than it keeps them, which limits growth and revenue.
Why it matters for apps
Churn quietly cancels out acquisition. If users leave as fast as they arrive, growth stalls no matter how much is spent on marketing.
- Churn rate: The main way to measure churn. Divide users lost in a period by users at the start of it. Track it per cohort, not only as one monthly total.
- Voluntary vs involuntary: Voluntary churn is a user choosing to leave or cancel. Involuntary churn comes from failed payments or expired cards, and needs a billing fix, not an engagement fix.
- Early churn: Many users leave in their first days, before they see value. Faster onboarding and early wins target this group.
- Watch the signals: Falling session frequency or skipped routines often appear before a user leaves. Act before they go quiet.
Industry examples
A streaming app targets subscribers whose viewing drops with a "finish your series" challenge (hypothetical).
A neobank gives users who have not paid by card in 30 days a goal to make three payments for a reward (hypothetical).
Build it with StriveCloud
StriveCloud does not calculate churn for you, but segments built on live stats flag users whose activity is falling, in real time. Reach them with push notifications or mail, and offer a comeback challenge with a scratchcard reward. Tier almost-lost notifications warn active users before they slip down a tier.
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Frequently asked questions
What is churn rate?
Churn rate is the percentage of users or customers who stop using a product or cancel during a set period. It shows how quickly a product loses its users.
How do you calculate churn rate?
Divide the number of users lost during a period by the number of users at the start of that period, then multiply by 100.
How can apps reduce churn?
Help users reach value fast, build regular habits, spot falling activity early, and give at-risk users a clear, rewarding reason to return. Fix failed payments separately.