How to build a weighted sales forecast
- Set the probability of closing for each stage of your sales process. The defaults are a common starting point; better still, use your own historical win rates by stage.
- Add your open deals with their value and current stage, or paste them from a spreadsheet or CRM export. Override the probability for any deal you know more about.
- The weighted forecast, commit and best-case totals update instantly, with the pipeline value in each stage. Download the result as CSV.
Weighted pipeline, commit and best case
A weighted forecast multiplies each deal's value by its probability of closing and adds them up: a 60,000 deal at 10% counts as 6,000, while a 24,000 deal in negotiation at 75% counts as 18,000. Across many deals the errors tend to cancel out, which makes the weighted total a reasonable estimate of what will close. For a single large deal it is less useful, because the deal will close at full value or not at all.
That is why sales leaders also look at commit, the deals the team is confident about, and best case, which adds the ones that could close with a push. Compare these with quota to see the gap. Forecast accuracy improves when stage definitions are strict (a "proposal" means a proposal has been sent, not discussed) and when probabilities come from your own data. Review stale deals regularly: an opportunity that has sat in one stage for months is usually less likely than its stage suggests. Data stays in your browser.
What is a weighted pipeline?
The sum of each open deal's value multiplied by its probability of closing.
Where do stage probabilities come from?
Ideally your CRM's historical conversion from each stage to closed-won. Otherwise start with typical values and adjust.
How accurate is a weighted forecast?
Fairly accurate for many similar-sized deals, much less so when one or two large deals dominate the pipeline.