Definition
Cohort month is the month index of a cohort relative to its start (month 0, month 1, month 2...). It is used to align retention curves.
Example
A cohort that started in March is in cohort month 2 in May, even if the calendar month is different.
How to use it
- Use cohort month to compare curves across different start dates.
- Report both cohort month and calendar month to avoid confusion.
- Keep the same cohort definition (signup vs first value) across reports.
Common mistakes
- Mixing cohorts defined by different start events.
- Comparing cohort month 1 in one report to calendar month 1 in another.
Why this matters
This term matters because small changes compound in SaaS metrics. Use consistent definitions by cohort and segment so you can diagnose retention, payback, and growth quality.
Practical checklist
- Write a 1-line definition for "Cohort Month" that your team will use consistently.
- Keep the time window consistent (weekly/monthly/quarterly) when comparing trends.
- Segment results (channel/plan/cohort) before drawing big conclusions from blended averages.
- Sanity-check with a related calculator from the same category on MetricKit.
- Read the related guide (e.g., Cohort analysis playbook: retention curves, LTV forecasting, and payback) for context and common pitfalls.
Where to use this on MetricKit
Calculators
- CAC Calculator: Calculate Customer Acquisition Cost (CAC) from total acquisition spend and new customers.
- Fully-loaded CAC Calculator: Calculate fully-loaded CAC by including paid spend plus sales & marketing costs (salaries, tools, and other acquisition costs).
- LTV Calculator: Estimate customer Lifetime Value (LTV) using ARPA, gross margin, and churn rate.
- LTV Sensitivity Calculator: See how gross profit LTV changes as churn and gross margin vary (simple 3x3 sensitivity).
- LTV:CAC Calculator: Compute LTV:CAC ratio and CAC payback using ARPA, gross margin, churn, and CAC.
Guides
- Cohort analysis playbook: retention curves, LTV forecasting, and payback: A practical cohort analysis workflow: build retention curves, forecast LTV, and translate retention quality into payback and growth decisions.