Three passes. First, cohort the churn: group customers by when they signed up and by what they did, then see whether people leave at month three or month eighteen, because those are completely different problems. Second, capture a structured reason at cancellation and classify it consistently, so 'too expensive' and 'missing feature' become countable rather than anecdotal. Third, actually interview a dozen churned customers, because the form answer is almost always the polite version. Then split the list into avoidable and not, and only spend effort on the avoidable half. Most teams do the first pass and stop.
4 hand-picked resources, 1 India-specific, 4 link-checked. Pick how you want to dig in.
Why we picked it Walks through building the cohort table itself, and separates acquisition cohorts from behavioural cohorts, which is the distinction that turns cohort analysis from a pretty chart into a diagnosis.
From Chargebee by Shaoli Paul 12 min read
Open chargebee.com →Why we picked it An actual interview script, twelve sections deep, designed to get past 'it was too expensive' to the real reason. This is the input your churn dashboard cannot give you.
From Klue by Adam McQueen 12 min read
Open klue.com →Why we picked it The ten strategies are sequenced the way you would actually run a churn programme: instrument, classify reasons, segment by whether you can influence it, then offer something reason-specific.
From Chargebee by Nupura Ughade and Arijit Bose 14 min read
Open chargebee.com →Why we picked it Zoho on the two churn predictors that actually work early (usage depth and NPS) plus a worked cohort example. Written for teams without a data function.
From Zoho Blog by Adhya 10 min read
Open zoho.com →How expansion, upsell and churn reads from a different seat.
The same ground, over in Grow & market, our Starting Up track.
The same ground, over in Grow organically & retain, our D2C track.
