Churn analysis identifies when and why visitors stop returning. If you had 1000 active users last month and 800 this month, 200 users churned (stopped visiting). Churn analysis explains why: did they unsubscribe? Did they switch to competitors? Did your site stop working for them? Understanding churn is more valuable than measuring retention because retention is just the inverse of churn.
Why churn matters
Focusing on new visitors while ignoring churn is expensive. If you acquire 100 new visitors but 80 existing users churn, you gained only 20 net users. Fix the churn problem first. Every churned user is a failure to satisfy someone who was already engaged.
Churn also reveals problems early. If churn suddenly spikes from 5% to 15%, something broke. Maybe a feature stopped working. Maybe traffic quality dropped. Churn is your early warning system.
How to measure churn
Simple churn rate: divide users lost by starting users. If you started with 1000 monthly users and ended with 800, you lost 200. Churn rate = 200 ÷ 1000 = 20% per month.
Voluntary vs involuntary churn: did the user choose to leave (unsubscribe, account deletion) or did they drop off naturally (no logins for 60 days)? Voluntary churn requires investigation. Involuntary churn may be fine if you reach out and re-engage them.
By segment: do free users churn faster than paid users? Do mobile users churn faster than desktop? Break churn down by user type to identify your biggest leaks.
Common reasons for churn
Site quality issues: performance is slow, features broke, design is confusing, mobile doesn't work. Users leave because the product fails them.
Needs changed: they found a better alternative. A competitor launched or improved. They changed industries or roles and your site no longer applies.
No clear benefit: they tried the site, didn't see value, and left. The site exists but they don't see why they should return.
Inactive communication: you stopped sending emails, publishing new content, adding features. The site feels abandoned. Users move on.
How to reduce churn
Monitor early warning signs: users who go from daily visits to zero visits in one week are about to churn. Reach out before they leave.
Survey churners: for users who unsubscribe or delete accounts, ask why. "Why are you leaving?" responses are gold — they tell you what to fix.
Fix quality issues immediately: if you find a performance bug, fix it fast. Every day that users experience a broken feature increases churn.
Activate dormant users: users with no logins for 30 days are at risk. Send them an email highlighting what they missed. Show them why they should return.
Remove friction from staying: don't require users to re-enter payment info every month. Don't force them through lengthy onboarding again. Don't hide their saved data or preferences. The easier you make it to stay, the lower your churn.
Is 10% monthly churn normal?
It depends on your business. Subscription services aim for 2-5% monthly churn. Content sites see 20-40% monthly churn (casual users). Free tools see 30-50% monthly churn. The key is trend: is your churn stable at 10% or is it growing from 5% to 10% to 15%? Growing churn is the problem.
How do I find out why a user churned?
For voluntary churn (unsubscribe, account deletion), ask in the cancellation flow: 'Why are you leaving?' For involuntary churn (no logins for 60 days), send an email: 'We noticed you haven't visited in a while. Everything okay?' Both approaches get honest feedback on what drove them away.
Should I track churn monthly or quarterly?
Monthly shows trends faster. If churn spikes in June, monthly tracking tells you in July. Quarterly tracking masks seasonal swings. Use monthly for monitoring, then calculate quarterly to smooth out noise.
What if my churn is zero (nobody leaves)?
Unlikely unless you have very small user base. More likely: your definition of 'active user' is too loose. Someone who visited 60 days ago may not be your baseline. Redefine active user as 'visited in the past 30 days'. Then recalculate churn. You will probably find some churn.
Can I predict who will churn?
Yes. Users with declining engagement (fewer logins each month) are at high risk. Users who skip features they used to use are at risk. Users who complained to support are at risk. Build a churn prediction score: flag users with 3+ risk signals and reach out proactively.
How much should I invest in re-engaging churned users?
The cost depends on their lifetime value. Users who paid $0 are cheap to replace. Users who paid $1000 are worth investing in to re-engage. For high-value churned users, invest in personal outreach: email, phone call, special offer. For low-value, send one re-engagement email and move on.