Features

This chapter covers the core features and capabilities of Metric Calculator.

Features

• 12+ SaaS metrics — MRR, ARR, ARPU, churn, revenue churn, NRR, LTV, CAC, LTV:CAC ratio, quick ratio, NPS, payback period
• Trend detection — Period-over-period change tracking with direction indicators
• Healthy range indicators — Know if your metrics are in the good, warning, or danger zone
• Multi-period analysis — Track metrics across months to spot trends
• Formula documentation — Every metric function explains WHY it matters, not just how to calculate it
• Pretty terminal output — Formatted metrics table with arrows and ranges
• JSON export — Machine-readable output for dashboards and automation

Requirements

• Python 3.10+
• No external dependencies (stdlib only)

Quick Start

Follow this guide to get Metric Calculator up and running in your environment.

Quick Start

# Calculate all metrics for the latest period
python src/metric_calculator.py --data examples/sample_subscriptions.json

# Show last 6 periods with trends
python src/metric_calculator.py --data examples/sample_subscriptions.json --periods 6

# Include CAC (provide total acquisition spend)
python src/metric_calculator.py --data examples/sample_subscriptions.json --acquisition-cost 15000

# Export to JSON
python src/metric_calculator.py --data data.json --output metrics_report.json

Input Format

JSON or CSV with period-level subscription data:

[
    {
        "period": "2026-01",
        "mrr": 42500,
        "new_mrr": 5200,
        "expansion_mrr": 1800,
        "contraction_mrr": 400,
        "churned_mrr": 1200,
        "total_customers": 185,
        "new_customers": 32,
        "churned_customers": 4,
        "revenue": 42500
    }
]