Cohort Analysis

Cohort analysis groups customers by a common attribute—typically the time period in which they signed up or made their first purchase—and tracks each group’s behavior over time. This approach isolates the experience of specific groups and reveals patterns that aggregate data obscures.

For example, comparing the 90-day retention rates of customers who signed up in January vs March might reveal that an onboarding improvement in February led to better retention for the March cohort. Without cohort analysis, this improvement would be invisible in aggregate retention numbers.

Cohort analysis is particularly valuable for subscription businesses because it shows whether newer customers are healthier than older ones. Improving cohort metrics over time (better retention, higher NPS, lower churn) indicates that your CX improvements are working for new customers even if legacy customer metrics lag.

Beyond time-based cohorts, behavioral cohorts (grouped by first feature used, onboarding path, or acquisition channel) and attribute cohorts (grouped by industry, company size, or plan tier) provide additional dimensions of analysis. Each cohort type answers different strategic questions.