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Skill 99 · Modeling Revenue Metrics
Subchapter 99.9
references/revenue-metric-definitions.mdMarkdown6 KBView on GitHub
Canonical definitions so every model computes the same number. Amounts assume the project base currency
(the amount column on revenue_item is already converted; see convertCurrency() in foundations for other
targets).
| Metric | Definition | Notes |
|---|---|---|
| Gross revenue | Sum of all revenue in a period, recurring + one-time, including negative amounts (refunds). | sum(amount) over revenue_item in the period. |
| MRR (Monthly Recurring Revenue) | Normalized recurring subscription revenue for a month. | Recognized recurring revenue per month = sum(amount) where is_recurring grouped by month on revenue_item (deferred revenue already spreads annual plans across their service period). The managed view is a , not history. |
mrr| ARR | MRR × 12. | A run-rate projection, not a forecast. |
| New MRR | MRR from customers who had no MRR in the prior period. |
| Expansion MRR | Increase in MRR from existing customers (upgrade/seat add). |
| Contraction MRR | Decrease in MRR from existing customers still paying. |
| Churned MRR | MRR lost from customers who cancelled or dropped to $0. | New − Contraction − Churn + Expansion reconciles the month-over-month MRR bridge. |
| Churn rate | churned_customers / total_customers in the period. | Revenue churn uses churned MRR / starting MRR. |
| ARPU | Average revenue per user in a period = total_revenue / active_users. | Across all revenue, not subscription-only. |
| LTV | ARPU / churn_rate. | Null when churn rate is 0; 0 when there’s churn but no revenue. |
New / Expansion / Contraction / Churn decompose the change in MRR between two months. Compute per customer:
m0, current-month recurring MRR m1.m0 = 0, m1 > 0 → New m1.m0 > 0, m1 > m0 → Expansion m1 - m0.0 < m1 < m0 → Contraction m0 - m1.m0 > 0, m1 = 0 → Churn -m0.starting_MRR + new + expansion - contraction - churn = ending_MRR. Use this identity as a validation
check on any MRR model.
Choose person vs group (B2C vs B2B) once. For account-level revenue use group_0_key (or the relevant
group_N_key) on revenue_item; for user-level use customer_id joined to persons via the customer
metadata link. Keep it consistent across MRR, churn, and LTV.