ReddRadar
Agent skill
cohort-analyzer
Analyzes revenue cohorts, retention curves, LTV/CAC trends over time
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/business/venture-capital/skills/cohort-analyzer
Metadata
Additional technical details for this skill
- domain
- business
- skill id
- vc-skill-011
- specialization
- venture-capital
SKILL.md
Cohort Analyzer
Overview
The Cohort Analyzer skill provides systematic analysis of customer and revenue cohorts to understand retention patterns, lifetime value trends, and business health over time. It enables deep understanding of unit economics evolution and customer quality.
Capabilities
Revenue Cohort Analysis
- Track revenue by acquisition cohort
- Analyze net revenue retention (NRR) by cohort
- Measure expansion, contraction, and churn
- Identify cohort quality trends over time
Retention Curve Analysis
- Build and visualize retention curves
- Compare retention across cohorts
- Calculate retention benchmarks by segment
- Identify retention inflection points
LTV/CAC Analysis
- Calculate LTV by cohort and segment
- Track CAC trends over time
- Analyze LTV/CAC ratio evolution
- Model payback period by cohort
Segment Analysis
- Segment cohorts by customer type
- Analyze channel-specific cohort quality
- Compare enterprise vs. SMB retention
- Identify highest-value customer segments
Usage
Analyze Revenue Cohorts
Input: Revenue data by customer and month
Process: Build cohort matrix, calculate retention
Output: Cohort analysis, NRR by cohort, visualizations
Build Retention Curves
Input: Customer data with start dates and activity
Process: Calculate retention by period since acquisition
Output: Retention curves, benchmark comparisons
Calculate Unit Economics
Input: Revenue cohorts, CAC data, time horizon
Process: Calculate LTV, LTV/CAC, payback
Output: Unit economics summary, trend analysis
Identify Cohort Trends
Input: Multi-period cohort data
Process: Analyze quality trends, flag concerns
Output: Trend analysis, quality assessment
Key Metrics
| Metric | Calculation | Target Range |
|---|---|---|
| NRR (Net Revenue Retention) | (Start + Expansion - Churn) / Start | 100-130%+ |
| GRR (Gross Revenue Retention) | (Start - Churn) / Start | 85-95%+ |
| LTV/CAC | Lifetime Value / Customer Acquisition Cost | 3x+ |
| Payback Period | Months to recover CAC | 12-18 months |
Integration Points
- Financial Due Diligence: Support revenue quality analysis
- Financial Model Validator: Validate retention assumptions
- Quarterly Portfolio Reporting: Track portfolio company cohorts
- Customer Reference Tracker: Connect qualitative feedback
Visualization Outputs
- Cohort retention heatmaps
- Retention curve comparisons
- LTV/CAC trend charts
- Cohort revenue waterfalls
- Segment comparison charts
Best Practices
- Use monthly cohorts for SaaS, adjust for business model
- Separate new logo vs. expansion revenue
- Analyze both count and revenue retention
- Look for cohort quality degradation as signal
- Segment analysis often reveals hidden patterns
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