Pipeline Quality & Scoring
More closed deals from the pipeline you already have.
- Pipeline-to-bookings from 1-in-5 to better than 1-in-3
- Forecast accuracy 65% to 90%+
- Sales cycle cut in half
The pipeline is full. Nothing closes. Everyone privately knows why.
Somewhere in your CRM right now there is a deal marked 60% that everyone knows is dead. It has been next quarter for three quarters. The rep believes, the manager does not push, and the forecast inherits the fiction.
Multiply that by every rep and you get the real problem: pipeline coverage looks fine, the forecast misses anyway, and the monthly call is a negotiation instead of a reading. The bottleneck is almost never the tool. It is that nobody ever defined what qualified means, so every rep defined it themselves, generously.
- 01Coverage says 3x and the quarter still misses
- 02“Is this deal real?” gets answered with a feeling
- 03Qualified means something different on every team, sometimes on every rep
- 04Stage progression is a rep's optimism, not an observed buyer behavior
- 05The forecast number changes depending on who is asking
What qualified means, in observable buyer behavior, not rep opinion. What a good deal looks like, from the deals you have actually won. This sounds trivial. It is the whole fight.
Aim the model at the serviceable market instead of the raw TAM, built off closed-won patterns, not a vendor's defaults.
A deal-inspection standard that reads the deal itself: stakeholders reached, problem pinned, decision process mapped. This is PLAN, the deal-craft move, run as a system, so the forecast stops being a poll.
What I hold loosely: the specific scoring model. Every one I have built got rebuilt within a year, because markets move. What I hold firmly: a pipeline where qualified is defined beats a bigger pipeline where it is not, every single time I have watched it play out.
The companies are on LinkedIn. Here, the work speaks without the logos.
Pipeline-to-bookings went from one in five to better than one in three, and forecast accuracy from 65% to 90%+ on a Deal Confidence Score, on an ICP and scoring model rebuilt from 1,000+ customer calls with Product, the data team and RevOps.
Scoring against the serviceable market took the core-segment win rate from roughly one in twelve to better than one in two, with the cycle cut in half.
- ×Not a CRM cleanup project.
- ×Not new stage names on the same fiction.
- ×Not a forecasting tool purchase: a tool on top of undefined words just automates the fiction.