Operating model: B2B data platform
Made by hand · pre-AIA monthly model for a B2B data platform that keeps ledger actuals and the forecast on one timeline, with revenue built from the funnel up and hiring driven by capacity.
Overview
This model ran a B2B data platform month to month. It had to answer how long the cash lasts and how much hiring the business can carry. Actuals and forecast share one monthly timeline, with actual months looked up from ledger exports by account code, so closing a month meant pasting an export.
How it's built
Revenue runs from marketing spend to leads, opportunities and bookings, then into cohorts by sign-up month, each with a billings ramp and retention curve. That volume sets how many reps and support staff the business needs, which switches on rows in a position-level hiring roster. Cost of sales prices transaction volume against a supplier tier table, so unit cost drops as volume grows. The expense build mirrors the chart of accounts, and each line is tagged with its forecast method.
What it shows
The summary tab reads runway and EBITDA breakeven live against today's date, next to burn levers like a hiring freeze. Each driver sits beside its historical actual, so stretch assumptions stand out. Unit economics sit on top, with CAC, cohort LTV and contracted ARR. The exit tab runs a venture cap table, and the round size flows back into cash on its closing date. The figures in the screenshots are disguised, and periods are shown as relative years (Y1, Y2) and months (M1, M2).
More on the approach behind both models: How I build models.