Operations Engine · plain-English guide
How to read Win/Loss
Win/Loss win/loss analyst. This guide explains what it produces, what each part means, and how it stays honest — so you can act on the output with confidence.
Takes
Deal outcomes
Gives
Pattern report
The data it uses: A closed-deal export — outcome plus the fields you track.
Watch how it works
How to read the output
Patterns
What separates wins from losses, each backed by deals and a sample size.
Reasons
The stated loss reasons — and whether the data backs them or they are just rep notes.
Do more / stop
Actions that trace to a pattern above, not generic sales advice.
The terms it uses
- Evidence-based reason
- A stated reason the data supports. The rest are unverified rep notes.
- Sample gate
- Below ~15 closed deals, patterns are hypotheses, not conclusions.
How it stays honest
Every agent separates what it measured from your data from what it inferred. You always know which is which.
Measured
- ✓Closed outcomes + fields
- ✓Win rate + sample size (computed)
- ✓Reported reasons
Inferred
- ~Pattern extraction
- ~Actions
- ~Which reasons are evidence-based
Questions people ask
Why distrust the recorded loss reason?+
Reps record the polite reason. The data often shows a different pattern — a competitor present, a size band, a cycle length.
Now read the real thing.
Run Win/Loss on your own data and compare the output to this guide. If it matches, you can trust it.