Weighted value of open opportunities. The Sales Pipeline Value Calculator takes prospecting stage value, prospecting close probability, qualified stage value, qualified probability, proposal stage value, proposal probability, negotiation stage value, negotiation probability and returns weighted pipeline value plus unweighted pipeline, weighted as a share of unweighted. Results update as you type, and the formula is shown under the result so you can repeat it in your own spreadsheet.
Pricing and sales metrics decide how much of the value you create you actually keep. Test price changes against margin, not volume alone, and measure the pipeline consistently so forecasts can be trusted. Use the worked example below to check the maths against your own figures.
How the Sales Pipeline Value Calculator works
Weighting each stage by its historical close rate turns a wish list into a forecast. Update the probabilities from your own closed-deal data every quarter.
Worked example
With the example values (prospecting stage value of $200,000, prospecting close probability of 10%, qualified stage value of $150,000, qualified probability of 30%, proposal stage value of $100,000, proposal probability of 60%, negotiation stage value of $50,000, negotiation probability of 90%), the weighted pipeline value is $170,000.00; unweighted pipeline $500,000.00, weighted as a share of unweighted 34%. Change any figure above and the result updates immediately; use Copy results to paste the summary into a note or email.
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Frequently Asked Questions
How is weighted pipeline value calculated?
weighted value = ∑ stage value × stage probability.
Which figures do I need?
Prospecting stage value, prospecting close probability, qualified stage value, qualified probability, proposal stage value, proposal probability, negotiation stage value, negotiation probability. Take them from the same period and the same set of accounts or reports so the ratio is consistent, and check the example values as a guide to the units expected.
Should I test a price change before rolling it out?
Yes. Model the margin impact here first, then test on a segment or product line and measure volume and margin before applying it everywhere.
