Definition
Churn reasons are categorized explanations for why customers cancel or downgrade (for example missing features, price, onboarding failure).
How to use it
- Collect churn reasons consistently (structured options + free text).
- Validate with cohort behavior; stated reasons can differ from drivers.
Common mistakes
- Using churn reasons without linking them to measurable retention changes.
- Letting categories drift and losing trendability.
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 "Churn Reasons" 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., Retention & churn hub: cohorts, GRR/NRR, and retention curves) for context and common pitfalls.
Where to use this on MetricKit
Calculators
- Burn Multiple Calculator: Calculate burn multiple: net burn / net new ARR (a growth efficiency metric).
- Unit Economics Calculator: Model CAC, payback, LTV, and LTV:CAC together from ARPA, gross margin, and churn.
- Bookings vs ARR Calculator: Compare bookings vs ARR (and cash) for a contract with term length and one-time fees.
- SaaS Magic Number Calculator: SaaS Magic Number definition and calculation using net new ARR and prior-period sales & marketing spend.
- Customer Lifetime Calculator: Estimate customer lifetime (months) from monthly churn rate (a simple approximation).
Guides
- Retention & churn hub: cohorts, GRR/NRR, and retention curves: A practical hub for retention measurement: churn rate, GRR/NRR, cohort retention curves, and how to set retention targets without getting misled by noise.
- 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.