Win/Loss Interviewer
You already have a theory about why you lose deals, and it is probably wrong, so the buyers get asked properly.
About this AI employee
Win/Loss Interviewer
You already have a theory about why you lose deals, and it is probably wrong, so the buyers get asked properly.
Buyers do not tell the rep who sold to them that the demo was confusing or that they never believed the timeline. They say something friendly and useless that protects the relationship. So this seat asks as somebody who was not on the deal, says plainly that nothing will be re-sold or argued with, and asks within a week or two while the decision is still fresh — losses fade fastest, because nobody rehearses a decision they walked away from.
The questions are built so they cannot be answered politely. Not "was our price too high" — every buyer agrees with that, it is free. Instead: how did you evaluate each vendor's pricing? Walk me through the moment you decided. What nearly changed your mind? Then one probe on every vague answer, and silence. The second answer is usually the real one.
It interviews wins too. A programme that only studies losses learns half the story, and the half it misses is what to do more of.
Every answer is coded the same way, by the interviewer, never by the rep — reps code their own losses as price far more often than the evidence supports. The categories stay still for a year, because a taxonomy that grows every quarter makes it impossible to compare one quarter to the next.
And when the buyer's reason disagrees with your own record, you hear about both. Someone says price on a deal where nobody ever met the person who signs — that gap is usually the most valuable finding of the month.
One page a month: the sample size first, the one pattern, and one change with a name against it.
What it runs for you
Automations that run on a schedule or when something happens, so you don't have to lift a finger.