cohortanalüüse

Cohort analysis is a type of behavioral analytics that breaks data down into related groups before analysis. These groups, or cohorts, each share common characteristics or experiences within a defined time frame. By tracking the behavior of these cohorts over time, businesses can gain valuable insights into customer engagement, retention, and lifetime value.

The fundamental principle of cohort analysis is to observe how a group of users, defined by a specific shared attribute (most commonly, their acquisition date), behaves over subsequent periods. For example, a cohort analysis might track users who signed up in January and observe their retention rates in February, March, and April. This contrasts with traditional analysis, which might look at all active users in a given month without differentiating their acquisition time.

Key applications of cohort analysis include understanding customer churn, measuring the effectiveness of marketing campaigns, identifying product improvements that impact user engagement, and forecasting future revenue. By segmenting users into cohorts, businesses can pinpoint specific points in the customer journey where users are dropping off or where engagement is particularly high. This allows for targeted interventions and more effective strategy development. The insights derived from cohort analysis are crucial for making data-driven decisions in areas like product development, marketing, and customer success.