`Weighted Win Rate = Closed Won Value / (Closed Won Value + Closed Lost Value)`
A team that wins 40% of its deals but only 22% of its dollars is losing its largest opportunities. That is a materially different problem from losing evenly across the book, and a count based rate will never show it.
Value inflation distorts both sides of the ratio
The calculation depends on amounts in the CRM being close to the amounts on the contract, and often they are not. ORM's position is that most deals close for less than the value they carry in the CRM, illustrated by a pipeline whose average deal size sits near 80,000 dollars against closed won deals averaging 40,000 dollars.
That gap has two effects. Closed lost records inherit the inflated amount, which pushes the denominator up and the weighted rate down. Open pipeline inherits the same inflation, so any forecast built from it overstates the number before win rate is applied at all.
The fix is to measure realization separately. Track closed won value against the amount recorded at a fixed reference point, such as entry into the first qualified stage, and carry that realization ratio into the forecast. See weighted pipeline for how the same correction applies to open deals.
Where to use each version
| Question | Use |
|---|---|
| How much revenue will this pipeline produce | Weighted win rate |
| Is qualification getting looser | Count based win rate |
| Are we losing the big deals | Both, and read the gap |
| Are reps discounting to close | Realization ratio, not win rate |
Putting it into the forecast
Applying a count based rate to a dollar pipeline assumes deal size is independent of outcome. It rarely is, because larger deals bring more stakeholders and more ways to end in no decision. Running the forecast on value weighted conversion, segmented by deal size band, removes an error that otherwise shows up every quarter in the same direction. That is a direct contributor to forecast accuracy, and it costs nothing beyond the query. See win rate for the underlying metric.
Frequently Asked Questions
What is the difference between weighted win rate and count based win rate?
Count based win rate treats every opportunity as one unit, so a 5,000 dollar deal and a 500,000 dollar deal carry the same weight. Weighted win rate divides won dollars by total closed dollars, so the answer reflects where the money actually went. A team can win most of its deals and still lose most of its addressable dollars.
Which win rate should you use in a forecast?
Use the value weighted version for revenue forecasting and the count version for process diagnostics. The forecast is a dollar question, so applying a count based rate to a pipeline with uneven deal sizes builds in an error the size of the size skew. Count based rates remain the right tool for comparing qualification and stage progression.
Should weighted win rate use the pipeline value or the closed value?
Track both, because the gap between them is a finding in itself. ORM's position is that most deals close for less than the value they carry in the CRM, illustrated by a pipeline averaging 80,000 dollars per deal against closed won deals averaging 40,000 dollars. If your denominator uses optimistic CRM amounts and your numerator uses real contract values, the rate will look worse than performance actually was, and the difference is a discounting and inflation measurement rather than a win rate measurement.
How does deal size skew break a weighted win rate?
One outsized deal can dominate a quarter's dollars and swing the rate on its own. Report weighted win rate alongside the count version and the largest single deal as a share of closed dollars. When the top deal is a large share of the total, read the count based rate as the more stable signal for that period.
Put these metrics to work
ORM builds custom revenue forecast models that turn concepts like weighted win rate into prescriptive action for your team.
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