Cohort analysis groups customers by when they started, the month they signed up, for example, and tracks how that specific group's behavior, retention, revenue, engagement, changes over time, rather than looking only at company-wide averages.
A blended, company-wide retention number can hide real trends: if a product improved significantly six months ago, customers who joined after that point should retain noticeably better than customers who joined before it, and a cohort view is what actually shows that difference. An average across all customers combined would just show a slow, murky improvement, or might mask it entirely.
This is why investors and operators increasingly ask for cohort-level retention curves rather than a single blended churn number: it separates whether a business is actually getting better at keeping customers from whether it's simply adding new customers fast enough to mask a stable or worsening churn problem underneath.
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