Business Metrics Calculator

When to use

• Preparing a board or investor deck and need accurately defined metrics
• The team disagrees on how a key metric (e.g., churn) should be calculated
• Benchmarking performance against industry standards
• Building a metrics report for a new business or new metric set
• Validating that existing metric calculations match the standard definition

Process

1. Identify the business model and period — confirm the model type (SaaS subscription, e-commerce, marketplace, product/app) and the calculation period (month, quarter, trailing 12M). Model type determines which metrics apply. See references/metric_definitions.md.
2. Load and validate the underlying data — check for expected row counts, missing values, and plausible date ranges. A metrics report is only as good as the data feeding it.
3. Calculate primary metrics — for SaaS: MRR, ARR, new MRR, churned MRR, expansion MRR, customer churn rate, revenue churn rate. For e-commerce: GMV, AOV, conversion rate, ROAS. Use scripts/saas_metrics.py or adapt for other models.
4. Calculate unit economics — LTV (simple average and cohort-based), CAC, LTV:CAC ratio, payback period, and quick ratio. Document which assumptions were used for LTV lifetime.
5. Compare to benchmarks — grade each metric against the industry benchmark thresholds in references/metric_definitions.md (good / average / poor). Flag anything outside the acceptable range.
6. Produce the metrics report — assemble results into assets/metrics_report_template.md with trend charts, benchmark comparison, and 3–5 key insights. Document any definition choices that differ from industry standard.

Inputs the skill needs

• Subscription or transaction data with at minimum: customer ID, date, value, status