Revenue Forecasting, Analytics, and KPIs
What this domain tests
This domain tests forecast construction, category discipline, accuracy measurement, and the KPI set that explains revenue movement. Expect ARR bridges, retention math, leading-versus-lagging indicators, and questions on forecast bias.
Core rules
- Categories need definitions: commit, best case/upside, pipeline, and omitted. A deal belongs in exactly one, and the definition is enforced in the CRM, not in the spreadsheet.
- Weighted pipeline is only as good as historical stage conversion. Recalculate probabilities from your own data each quarter.
- Accuracy and bias are different metrics. Accuracy is measured by mean absolute percentage error; bias is the persistent direction of misses. Consistent over-calling and consistent under-calling require different fixes.
- ARR bridge is the core analytical object: starting ARR + new + expansion − contraction − churn = ending ARR.
- NRR versus GRR: NRR includes expansion and reveals whether the base grows; GRR excludes expansion and exposes pure leakage. Report both.
- Leading indicators (pipeline coverage, early-stage conversion, product adoption) move before revenue; lagging indicators confirm it.
- Cohort analysis separates vintage quality from aggregate noise.
Worked example
Start ARR $10.0M, new $2.0M, expansion $1.0M, contraction $0.5M, churn $0.8M → ending ARR $11.7M. NRR = (10.0 + 1.0 − 0.5 − 0.8) ÷ 10.0 = 97%. GRR = (10.0 − 0.5 − 0.8) ÷ 10.0 = 87%. Reading: the installed base shrinks 3% net and 13% gross, so all growth came from new logos. The retention problem, not the sales engine, is the flag - and it will compound against future growth.
Traps
Mixing bookings into an ARR bridge. Quoting NRR when the question is gross leakage, since expansion masks churn. Over-weighting late-stage optimism. Reporting accuracy without direction of bias. Treating a single strong quarter as a trend.