Sales Forecasting
Sales forecasting is the practice of predicting future revenue based on the current pipeline, deal stages, and historical close rates.
Last updated July 18, 2026
How sales forecasting works
A sales forecast estimates future revenue by applying a probability to each open deal and summing the results. The simplest version multiplies each deal's value by a win probability tied to its current stage — a deal in "Proposal Sent" might carry a 40% probability, while one in "Verbal Commit" might carry 80%. More advanced forecasts weight those probabilities using historical data: if deals in a given stage have closed 35% of the time over the last two quarters, that rate replaces a guessed number.
The three common forecasting methods are:
- Stage-based (weighted pipeline): each deal stage has a fixed win probability, and forecast value is deal value times stage probability, summed across all open deals.
- Historical/trend-based: the forecast looks at closed-won revenue over past periods and projects forward, adjusted for pipeline growth or decline.
- Rep-level rollup: individual reps commit to what they expect to close, and those commitments are aggregated into a team forecast, often alongside the stage-based number as a sanity check.
Why sales forecasting matters
A forecast is only useful if it changes a decision — hiring, spend, or where a manager spends coaching time. Without one, a sales leader is reacting to whether the quarter hit target instead of seeing the shortfall three weeks out, while there's still time to add pipeline or push stalled deals. A forecast also surfaces which deals are inflating the numbers: a single large deal sitting in "Negotiation" for 90 days past its original close date skews the total and usually signals it needs attention, not optimism.
Forecasting also depends entirely on data quality in the CRM. If reps don't update deal stages or close dates, the forecast reflects wishful thinking rather than pipeline reality — which is why forecasting accuracy is often less a sales problem than a CRM adoption problem.
Example
A team with $500,000 in open pipeline split across three stages — $200,000 in "Qualified" (20% probability), $200,000 in "Proposal Sent" (40%), and $100,000 in "Verbal Commit" (75%) — has a weighted forecast of $40,000 + $80,000 + $75,000 = $195,000 for the period, even though total pipeline value looks five times larger.
Forecasting vs. pipeline value
Total pipeline value and a sales forecast are not the same number, and treating them as interchangeable is a common mistake. Pipeline value is the sum of every open deal regardless of how likely it is to close; the forecast discounts that sum by probability of closing. A team can have a large, healthy-looking pipeline and still forecast well below target if too many deals sit in early stages with low win probability — which is exactly the gap a forecast is meant to expose before quarter-end.