The Forecast Audit: Commit vs. Best Case vs. Pipeline
Ask five reps on the same team what separates a "commit" deal from a "best case" one, and you'll often get five different answers. When forecast categories mean different things to different people, the number leadership presents to the board is really an average of everyone's individual optimism, not a real forecast, and nobody can point to exactly where that gap came from.
Run this short audit against your own pipeline to see where the categories are actually breaking down, before the drift shows up as a missed number at quarter end.
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Step One: Write Down What Each Category Is Supposed to Mean
Before checking anyone's deals, write a specific, one-sentence definition for each category. Commit might mean a confirmed economic buyer, agreed pricing, and a paper process already underway. Best case might mean strong interest and a plausible path to close this quarter, but missing one of commit's requirements. Pipeline is everything else that's genuinely active. If you can't write these definitions in a sentence each, that's the first sign the categories aren't well defined yet.
A written set of definitions might read like this:
- Commit means a confirmed economic buyer, agreed pricing, and a paper process that is already underway.
- Best case means strong interest and a plausible path to close this quarter, but missing at least one commit requirement.
- Pipeline means everything else that is genuinely active, with a real reason to believe the deal is alive.
- Every definition fits in one specific sentence, so any rep can apply it the same way as any other.
Step Two: Pull Ten Commit Deals and Check Them Against the Definition
Go through ten deals currently marked commit and check each one honestly against your written definition. Is there really a confirmed economic buyer, or is that assumed based on an enthusiastic contact? Is pricing actually agreed, or still being discussed? Count how many of the ten genuinely meet the bar. If it's meaningfully less than ten, you have a calibration problem, not just a few optimistic reps.
Step Three: Compare Categories Across Reps, Not Just Within One Person's Pipeline
The real value of this audit shows up when you compare how consistently different reps apply the same category. If one rep's commit deals reliably meet the bar and another's rarely do, that's a coaching conversation about qualification standards, not a forecasting quirk to route around with a discount factor applied to that person's number.
Step Four: Check Historical Accuracy by Category
Pull last quarter's forecast categories and compare them against what actually closed. What percentage of commit deals from three months ago actually closed as commit, versus slipping or dying? Do the same for best case. A win rate near 19 percent1 on new logos is a useful outside reference point, if your commit category is converting at a rate far below what a reasonably confident category should produce, the definition or its enforcement needs work.
Step Five: Fix the Definition, Then Re-Audit Next Quarter
Once you've found the gaps, tighten the written definition and walk the team through specific examples of deals that do and don't qualify for each category. This isn't a one-time fix. Run the same short audit again next quarter to check whether the tightened definitions actually held, or whether the same drift crept back in once the initial attention faded.
What the Audit Found on One Real Team
Say a manager runs this audit and pulls ten commit deals. Seven genuinely meet the written bar: confirmed economic buyer, agreed pricing, paper process underway. Three don't, and in each of those three, the gap is the same one: no confirmed economic buyer, just an enthusiastic mid-level contact the rep assumed had signing authority.
That's not three unrelated mistakes, it's one recurring blind spot, and it points to a specific, fixable training gap rather than three isolated judgment calls. The manager adds a single required question to the qualification checklist, "has the buyer explicitly confirmed who signs," and re-runs the same audit the following quarter. The number of genuine commit deals climbs from seven out of ten to nine out of ten, not because reps got better sellers, but because the definition finally caught the one gap that kept recurring.
The useful part of this exercise wasn't the initial score, it was finding a single, specific, repeated gap hiding underneath what looked like scattered individual misjudgments. Most audits like this surface one or two recurring patterns rather than a long list of unrelated issues, and fixing the pattern moves the whole team's forecast accuracy more than coaching each deal individually ever would.
What Good Looks Like
A well-calibrated forecast has written, specific definitions for each category that reps apply consistently, and a commit category that historically converts at a rate meaningfully higher than best case or general pipeline.
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How to Get Started
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Pipedrive's reporting can show historical conversion rates by forecast category, which makes it straightforward to check whether commit deals are actually converting at the rate the label implies.
Close lets you track category changes over a deal's lifecycle, so you can see exactly when and how often a deal moved between commit, best case, and pipeline before it closed or died.
Frequently Asked Questions
How long does this audit actually take?
Checking ten commit deals against a written definition and comparing them across a few reps is realistic to do in well under an hour once the definitions themselves are written. Writing the definitions the first time takes longer, since it usually surfaces disagreement within leadership too.
Should every sales team have the same forecast categories?
The category names, like commit, best case, and pipeline, are common enough to reuse. What matters more is that your specific definitions match your own sales process and get applied consistently, rather than copying another company's definitions that assume a different buying process.
What's the biggest sign that categories have drifted?
A commit category that historically converts at a rate well below what the label implies is the clearest sign. If commit deals close at roughly the same rate as best case deals, the two categories aren't actually distinguishing anything meaningful.
Sources
Where we quote a benchmark, we show its source. Other figures in this guide are estimates or general guidance, so check them against your own numbers.
- Average B2B new-logo win rate. Ebsta x Pavilion 2025 GTM Benchmarks Report, 2025.
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