cohort-analyzer
Analyzes revenue cohorts, retention curves, LTV/CAC trends over time
它会碰到什么
这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。
技能内容
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
想直接用这个技能?
本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。
它属于哪个仓库
library/specializations/domains/business/venture-capital/skills/cohort-analyzer/SKILL.md