mcpbeat

Saas Metrics Coach

borghei/saas-metrics-coach

> This skill should be used when the user asks to "calculate MRR", "analyze churn", "compute SaaS metrics", "do cohort retention analysis", "calculate LTV or CAC", "evaluate unit economics", or "track subscription revenue growth".

13k tokens
context cost
the whole folder, loaded on every use
7
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
447
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/borghei/Claude-Skills --skill saas-metrics-coach

What comes with it

47 041 bytes besides the instruction
examples/cohorts.csv
examples/subscriptions.csv
references/saas-metrics-guide.md
scripts/cohort_analyzer.py
scripts/mrr_calculator.py
scripts/unit_economics.py

The instruction itself

16 sections, as written by the author

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.

Clarify First

Before calculating, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • [ ] Which metric set — MRR/ARR growth, cohort retention, or unit economics (selects the script and the input format: subscription CSV, activity CSV, or metrics JSON)
  • [ ] Reporting period + currency handling — the window and how multi-currency MRR is normalized (changes every revenue and churn figure)
  • [ ] Gross margin — the margin to apply (drives LTV and CAC payback; LTV = ARPU x margin / churn)
  • [ ] Churn definition — gross vs. net, logo vs. revenue (changes churn rate, NRR, and the health-flag verdict)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

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

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

Workflow 2: Investor Deck Preparation

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

Workflow 3: Churn Investigation

  • Run mrr_calculator.py with --breakdown to see churn by plan tier
  • Run cohort_analyzer.py to identify which cohorts churn fastest
  • Cross-reference cohort drop-off periods with product changes
  • 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% |

How to use it

Copy the folder

Take borghei/saas-metrics-coach from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.