Agent Skills: SaaS Metrics Coach Skill

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financeID: aaaaqwq/claude-code-skills/saas-metrics-coach

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skills/saas-metrics-coach/SKILL.md

Skill Metadata

Name
saas-metrics-coach
Description
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SaaS Metrics Coach Skill

Overview

Production-ready SaaS metrics toolkit for calculating MRR/ARR, analyzing cohort retention, and evaluating unit economics. Designed for SaaS founders, finance teams, and growth operators who need precise subscription revenue analysis without spreadsheet gymnastics.

Quick Start

# Calculate MRR, ARR, growth rate, and churn from subscription data
python scripts/mrr_calculator.py subscriptions.csv

# Run cohort retention analysis
python scripts/cohort_analyzer.py users.csv --cohort-period monthly

# Calculate LTV, CAC, LTV:CAC ratio, and payback period
python scripts/unit_economics.py metrics.json

Tools Overview

| Tool | Purpose | Input | Output | |------|---------|-------|--------| | mrr_calculator.py | MRR, ARR, growth rate, churn | CSV with subscription data | Revenue metrics + trends | | cohort_analyzer.py | Cohort retention analysis | CSV with user signup/activity data | Retention matrix + curves | | unit_economics.py | LTV, CAC, LTV:CAC, payback | JSON with acquisition/revenue data | Unit economics dashboard |

Workflows

Workflow 1: Monthly SaaS Health Check

  1. Export subscription data as CSV (columns: customer_id, plan, mrr, start_date, end_date)
  2. Run mrr_calculator.py to get current MRR, ARR, net new MRR, churn rate
  3. Run cohort_analyzer.py on user activity data to identify retention trends
  4. Run unit_economics.py to validate LTV:CAC ratio stays above 3:1
  5. Review output for warning flags (churn > 5%, LTV:CAC < 3, payback > 18 months)

Workflow 2: Investor Deck Preparation

  1. Run mrr_calculator.py --format json to get growth metrics for charts
  2. Run cohort_analyzer.py --format json for retention curves
  3. Run unit_economics.py --format json for unit economics summary
  4. Use JSON output to populate investor deck data points

Workflow 3: Churn Investigation

  1. Run mrr_calculator.py with --breakdown to see churn by plan tier
  2. Run cohort_analyzer.py to identify which cohorts churn fastest
  3. Cross-reference cohort drop-off periods with product changes
  4. Identify if churn is concentrated in specific segments or time windows

Reference Documentation

Key SaaS Metrics Definitions

  • MRR (Monthly Recurring Revenue): Sum of all active subscription revenue normalized to monthly
  • ARR (Annual Recurring Revenue): MRR x 12
  • Net New MRR: New MRR + Expansion MRR - Churned MRR - Contraction MRR
  • Gross Churn Rate: Lost MRR / Beginning MRR for the period
  • Net Revenue Retention (NRR): (Beginning MRR + Expansion - Churn - Contraction) / Beginning MRR
  • LTV (Lifetime Value): ARPU / Monthly Churn Rate (simplified) or ARPU x Gross Margin / Churn
  • CAC (Customer Acquisition Cost): Total Sales & Marketing Spend / New Customers Acquired
  • LTV:CAC Ratio: Target 3:1 or higher for healthy SaaS
  • CAC Payback Period: CAC / (ARPU x Gross Margin) in months

See references/saas-metrics-guide.md for comprehensive framework details.

Common Patterns

Pattern: Subscription CSV Format

customer_id,plan,mrr,start_date,end_date,status
C001,pro,99.00,2025-01-15,,active
C002,basic,29.00,2025-02-01,2025-08-15,churned
C003,enterprise,499.00,2025-03-10,,active

Pattern: User Activity CSV Format

user_id,signup_date,last_active_date,activity_month
U001,2025-01-05,2025-06-15,2025-06
U002,2025-01-12,2025-03-20,2025-03

Pattern: Unit Economics JSON Format

{
  "period": "2025-Q4",
  "total_customers": 1200,
  "new_customers": 150,
  "churned_customers": 45,
  "total_mrr": 89500.00,
  "arpu": 74.58,
  "gross_margin": 0.82,
  "sales_marketing_spend": 45000.00,
  "monthly_churn_rate": 0.0375
}

Healthy SaaS Benchmarks

| Metric | Concerning | Acceptable | Strong | |--------|-----------|------------|--------| | Monthly Churn | > 5% | 2-5% | < 2% | | Net Revenue Retention | < 90% | 90-110% | > 120% | | LTV:CAC | < 1:1 | 1:1-3:1 | > 3:1 | | CAC Payback | > 24 mo | 12-18 mo | < 12 mo | | Gross Margin | < 60% | 60-75% | > 75% |