Customers are leaving — quietly, without complaint, and often before they've generated enough value to cover what it cost to acquire them. Churn analysis is how you find out who's leaving, when, and why — and what to do about it. In this video, I break it down using a fitness app as our example, and walk through everything: how to calculate churn rate, how to read a survival curve, how to segment and diagnose churn, and how to find the warning signs before a customer actually cancels.
By the end, you'll understand:
✅ The churn rate formula — and why even small monthly churn compounds fast
✅ The difference between voluntary and involuntary (passive) churn
✅ The survival curve — and what its shape tells you
✅ Early vs. late churn — two completely different problems with different fixes
✅ How to segment who churns before diagnosing why
✅ How to map the timing of churn to find specific trigger moments
✅ The exit survey — how to turn a number into a list of fixable causes
✅ Leading indicators — how to spot churn before it happens and intervene early
✅ Why passive churn is recoverable — and how a dunning campaign works
Perfect for beginners — especially useful for subscription businesses, apps, and loyalty programs.
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