Cohort Analysis is an analytical technique that groups customers based on a shared characteristic — most commonly the date of their first purchase — and then tracks their behavior over subsequent time periods.
Instead of looking at all customers as a single blob, cohort analysis lets you answer questions like:
- "Are customers acquired in January more valuable than those acquired in March?"
- "Is our 90-day retention rate improving or declining over time?"
- "Which marketing campaigns bring in customers that stick around?"
How it works in e-commerce:
- 1Define your cohort (e.g., all customers who made their first purchase in January 2024)
- 2Track a metric over time (e.g., repeat purchase rate, cumulative revenue)
- 3Compare cohorts against each other
This reveals trends that aggregate metrics hide. For example, your overall revenue might be growing, but cohort analysis could reveal that each new cohort is actually less valuable than the previous one — a critical warning sign that would be invisible in top-level dashboards.
Cohort analysis is especially valuable when combined with customer segmentation, as it shows whether your segmentation strategies are actually improving customer quality over time.
