What is Cohort Analysis?
Grouping customers by when they started and tracking each group over time - the clearest view of retention.
Cohort Analysis: definition
Aggregate metrics can mask what is really happening: total revenue can rise even as newer customers churn faster. Cohort analysis fixes this by following each acquisition group separately - the January cohort, the February cohort - and watching their retention or spend month by month. It reveals whether the business is genuinely improving retention, and it underpins lifetime value and payback calculations.
- Groups customers by acquisition period (or another shared trait)
- Tracks retention, revenue, or churn for each group over time
- Exposes trends that blended averages hide
- Foundational for LTV, payback, and net revenue retention
How Fintra handles it
Because Fintra holds revenue and customer data on one model, cohorts can be built from actual billing history rather than a separate analytics export. Retention and revenue curves by cohort feed LTV, CAC payback, and net revenue retention, so the growth metrics are grounded in the same numbers as the financials.
- Cohorts built from actual billing and customer records
- Retention and revenue curves tracked per cohort
- Feeds LTV, payback, and retention metrics consistently
Worked example
| Cohort | Month 0 | Month 3 | Month 6 |
|---|---|---|---|
| January | $10,000 | $9,000 | $8,200 |
| February | $12,000 | $11,200 | $10,600 |
| March | $14,000 | $13,500 | - |
Frequently asked questions
What is a cohort in cohort analysis?
A cohort is a group of customers or users who share a common starting point - most often the month or quarter they were acquired. Tracking each cohort separately over time shows how behavior evolves for that specific group rather than for the customer base as a whole.
Why is cohort analysis better than overall averages?
Because blended averages can hide divergent trends. Total revenue can grow while newer customers retain worse, or vice versa. Cohort analysis separates these effects, revealing whether retention and monetization are genuinely improving over time.
What can cohort analysis measure?
Retention, revenue expansion or contraction, churn, and lifetime value by acquisition group. It can also segment by channel, plan, or region. The common thread is following a defined group over time to understand behavior that averages obscure.
How does cohort analysis relate to net revenue retention?
Net revenue retention is essentially a cohort measure - it tracks how the revenue from an existing group of customers changes over time, including expansion and churn. Cohort analysis provides the underlying curves that NRR summarizes into a single figure.
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