Why cohort-based LTV beats flat-churn LTV
Flat-churn LTV uses a single monthly churn rate (ARPU × margin ÷ churn) and assumes the rate is constant across customer age. It's a useful back-of-envelope, but it overstates true LTV by 25–40% for most SaaS — because retention curves bend. Customers who stick past month 3 are dramatically more likely to stick at month 12. Flat-churn ignores this.
The cohort method
Cohort LTV sums each cohort's actual retention curve, weighted by ARPU and margin, projected forward. The result is the dollar value a customer is expected to generate, given how the customer base actually decays — not how a uniform churn rate would predict.
Reading the heatmap
Each row is a monthly cohort. Each column is age in months. Darker accent = higher retention. Three things to look for: (1) whether newer cohorts retain better than older ones (product-led improvement), (2) the "leak month" where the steepest drop occurs (typically month 1–2 onboarding), (3) whether decay flattens after month 3 (signal of true product-market fit).
2024 SaaS retention benchmarks
- SMB SaaS — month 1 retention 80–90%, month 12 retention 50–65%.
- Mid-market — month 1 retention 92–97%, month 12 retention 80–88%.
- Enterprise — month 1 retention 97–99%, month 12 retention 90–95%.
When to trust this analysis
With fewer than 50 customers per cohort, retention curves are statistically noisy — single cancellation swings can mislead you. For low-volume SaaS, focus on the trend across cohorts (improving or worsening) rather than the absolute curve shape.
Companion tools
Feed the cohort-true LTV into the CAC Payback Calculator for a payback math that doesn't overstate, grade the same retention engine via Quick Ratio + NRR in the MRR Health Snapshot, project the resulting growth against cash with the Runway Calculator, and stack the retention pillar against investor stage bands using the Fundability Scorecard.
Related reading
Context on why MRR is the operator's number when cohort variance is high: MRR vs ARR for bootstrapped founders. Runway implications when retention bends the wrong way: The SaaS Runway Playbook.