Revenue Forecast Builder Prompt
Prompt
Build a revenue forecast. Business model: [SaaS / transactional / services / e-commerce] Current monthly revenue: [amount] Revenue drivers: [new customers, upsell, churn, pricing] Historical growth: [MoM or YoY rate] Upcoming changes: [new product, price change, expansion] Please build: 1. Key assumptions the forecast depends on 2. Conservative, base, and optimistic scenarios 3. Break-even point 4. The assumption with most impact on the forecast 5. Sensitivity table: how does revenue change if [key assumption] shifts 10%?
Why it works
Building the forecast around the specific revenue drivers for the business model — MRR movement for SaaS, conversion funnel for e-commerce, pipeline for services — produces a forecast that can be updated when assumptions change rather than a static spreadsheet. The assumption sensitivity section identifies which inputs have the most impact on the output, which directs forecasting effort toward the variables that matter most. Including both base and scenario cases gives leadership a range rather than a false precision single number.
Watch out for
Revenue forecasts that are presented without explicit assumptions create the conditions for forecast disputes when actuals diverge — leadership will attribute the miss to execution rather than assumption changes if the original assumptions aren't documented. Date and version your forecast assumptions every time the model is updated so the narrative of why the forecast changed is preserved alongside the numbers.
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