Build funnel metrics the meeting will actually trust.
“Where does our funnel actually leak, and can we agree on what the metrics even mean?”
Conversion by stage, velocity, and win rate with every definition pinned, and the leak named.
What this skill does
Reads your stage data and builds the core funnel: how many deals convert from each stage to the next, how long they sit in each stage, what share of qualified deals win, and where the biggest drop-off is. Every metric ships with its definition attached, so the conversation is about the leak, not about whether the number is real.
Inputs
- Works today with: a CSV or paste of deals with stage, amount, created date, close date, stage-entry dates if you have them, and won/lost outcome.
- More powerful connected to a CRM: it reads the full deal history and stage timestamps automatically, across every cohort.
- Sharper with a data warehouse: it can build true entered-stage cohorts instead of inferring from a current snapshot.
- Sharper with a BI tool: pushes the pinned definitions into a dashboard so the whole team reads one number.
How it works
- 1Stage-to-stage conversion
For each adjacent stage pair, divide deals that reached the later stage by deals that entered the earlier one. State the denominator out loud. A rate that divides by "all deals ever" and a rate that divides by "deals that entered this stage" are different numbers, and only one of them is honest about the leak.
- 2Time-in-stage velocity
Measure median days in each stage, not mean. One 400-day zombie deal drags a mean and hides the typical path. Use stage-entry timestamps where you have them and say so where you had to infer from close date.
- 3Win rate
Win rate is wins divided by resolved deals (won plus lost), with no-decisions handled explicitly and stated. Report it on a trailing window big enough to mean something, never on this week's handful.
- 4Leak detection
Rank the stage transitions by drop-off and name the single worst one. The biggest leak is where the funnel loses the most deals relative to what entered, not the stage with the lowest raw count. That is the one place a fix moves the whole number.
- 5Definition ledger
Every metric prints with its definition and denominator beside it. This is the trust layer. When someone questions a number in the room, the answer is already on the page.
Output format
FUNNEL METRICS · created Q cohort · 620 deals
Transition Conversion Median days Note
Lead -> Qualified 44% 9 denom: leads created
Qualified -> Demo 71% 6 denom: entered Qualified
Demo -> Proposal 52% 14 biggest leak
Proposal -> Won 61% 11 denom: entered Proposal
Win rate (trailing 2Q): 34% of resolved deals. No-decisions excluded, counted separately.
Biggest leak: Demo -> Proposal. Half of demoed deals never get a proposal.
Next: capture stage-entry timestamps to replace inferred velocity on 2 stages.
Illustrative figures. Your run reports your real numbers.
Tips
- Every rate shows its denominator. No naked percentages.
- Velocity is median, and the date basis is named.
- Win rate states how no-decisions were handled, every time.
- Small samples are flagged, not smoothed. A rate on nine deals says so.
Turn a messy CRM into a ranked cleanup list.
Finds the hygiene problems that break reporting first: missing fields, stale records, duplicates, and bad stages, before the cosmetic ones.
Forecast a defensible range, not a hero number.
Category definitions, coverage math, historical conversion, and a low / likely / high range vs quota.