In brief: Cohort analysis tracks the behaviour of customer groups that share an initial event or characteristic, such as the month of their first order, a product or an acquisition source.
How I use cohort analysis in practice
In practice, I do not use cohort analysis as just another number in a presentation. I first decide which decision it should make more precise, which data or observations support it, and who will change something in response to the result. I define the starting point, timeline and outcome consistently for every group, and compare retention, margin or activation at the same cohort age. I also record the baseline, measurement date and limits of interpretation. This makes it possible to distinguish a real improvement from a change in the tool, sample or wording of the question.
What to watch for
The greatest risk is apparent precision. Cohorts with few cases can look dramatic, and a change in the customer mix is easily mistaken for a change in the product. I therefore compare the result over time, on a stable sample and alongside the commercial context. If the term does not lead to a concrete next step, it has not produced analysis; it has only created another label.
Questions for decisions
- What exactly determines membership in a cohort?
- Are we comparing groups at the same age?
- Is the sample large enough?
- Which process change explains the difference?