What is Cohort analysis?
Cohort analysis is grouping customers by a shared starting point, such as the month of their first order, and tracking how each group behaves over time.
It answers questions that blended averages hide. For example, whether customers acquired in one season reorder as often as those acquired in another, or whether a new welcome flow changed repeat purchasing for people who joined after it launched.
Cohorts can be defined by signup month, first purchase month, first product bought or acquisition source. Each is then followed across later months for repeat orders or engagement.
The main caution is sample size. A very small cohort will swing from month to month, so avoid drawing strong conclusions from it.
A worked example.
Imagine a hypothetical skincare store comparing customers whose first purchase was a starter set with those whose first purchase was a single serum. Tracking both groups across later months shows which entry product leads to more reorders, guiding what the welcome flow promotes.
Common mistakes.
- Drawing conclusions from very small cohorts
- Mixing different acquisition channels in one cohort
- Comparing cohorts of different ages as if equal
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