Cohort Logo and Revenue Retention Analysis
Build logo and revenue retention grids, isolate churn versus expansion, and pinpoint the cohort ages where revenue leaks.
Before & after
Same prompt, same agent — the only difference is the skill.
Cohort analysis can be useful for understanding retention. You'll want to look at groups of customers acquired in the same time period and track how they perform over time. Retention is important for recurring revenue. Different cohorts might have different retention rates depending on when they were acquired or what they signed up for. Analyzing these patterns can help you identify trends. You could look at monthly or quarterly cohorts depending on your business. What metrics are most important for you to track?
COHORT REVENUE RETENTION MODEL (sample data, illustrative)
ACQUISITION COHORT: Q1 2026 (100 customers, 50k MRR)
QUARTER-BY-QUARTER REVENUE RETENTION (logo retention shown below)
Q1 Q2 Q3 Q4
Cohort1: 100% 87% 72% 60%
Cohort2: 100% 91% 79% 66%
Cohort3: 100% 84% 68% 55%
Avg: 100% 87.3% 73% 60.3%
REVENUE RETENTION (same cohorts, net-dollar basis after upsells)
Q1 Q2 Q3 Q4
Cohort1: 100% 94% 84% 78%
Cohort2: 100% 96% 89% 82%
Cohort3: 100% 92% 81% 74%
Avg: 100% 94% 84.7% 78%
REVENUE LEAKAGE ANALYSIS:
Q2 avg MRR loss: 6,500/quarter (logo churn + downgrades)
Q3 avg MRR loss: 9,100/quarter (acceleration signal)
CHURN PATTERN:
Months 0-3: 13% loss (adoption friction)
Months 3-6: 8% loss (settling in)
Months 6-12: 7% loss (mature cohort)
UPSELL LIFT:
• Cohort2 outperforms on net-dollar (means better expansion)
• Cohort2 acquired Feb (post-price-increase) → higher initial spend holds better
ACTION: Investigate Feb 2026 onboarding improvements; replicate for future cohorts.
Quality metric: 'Net dollar retention' (78% for mature cohorts) indicates revenue plateau risk.About this skill
Revenue looks stable, but are customers staying, or are a few expanding accounts covering the losses? This skill builds comparable logo and revenue retention curves and traces the gap back to customer losses, contraction, expansion, and reactivation.
What it does
- Defines acquisition cohorts, baseline revenue, active customers, and observation windows before calculating retention.
- Builds age-aligned logo and revenue retention grids with unobserved periods clearly marked.
- Normalizes recurring revenue so annual payments, invoice timing, and proration do not create false churn.
- Reconciles retained revenue to baseline dollars through expansion, contraction, and churn.
- Separates customer-weighted and revenue-weighted results, including large-account concentration.
- Identifies the lifecycle ages where losses concentrate and the next investigation supported by the evidence.
What you get
A cohort model with retention grids, curve specifications or charts when supported, and a short financial diagnosis. If source data is incomplete, you get a provisional model with explicit assumptions and the exact fields needed to finish it.
Best for
Finance, growth, and customer success teams investigating subscription retention, acquisition quality, or stable revenue that may be hiding customer churn.
SKILL.md preview
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name: cohort-logo-and-revenue-retention-analysis
description: Builds age-aligned customer and revenue retention grids from customer-level data, using fixed cohort denominators, normalized revenue, and reconciled churn and expansion bridges. Use when the user says "build a cohort revenue model", "show logo and revenue retention", "our revenue is flat but customers keep leaving", "compare acquisition cohorts", "is expansion hiding churn?", "my retention heatmap keeps changing", or "where are we leaking recurring revenue?".
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# Cohort Logo and Revenue Retention Analysis
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