A written model of your GTM
What each stage, metric and record means and how they connect, stored where AI can read it. Nobody re-teaches it.
How we work · What we build · Step 02
Know what's working, why, and what it's worth
Ask in plain English and get an answer that uses your definitions, shows its working, and says what the gap is worth. Built on your GTM data warehouse.
Book a call30 min · no prep needed
What you're after
01
The leak, in dollars
The stage and the lever where the most revenue is lost, ranked.
02
Numbers people believe
One definition of qualified and one definition of a meeting, used by every report and every agent.
03
Answers you can check
Each one shows the tables, definitions and filters behind it.
Questions your team asks, and what comes back
Illustrative. Companies, people and numbers are fictional.
| Question | What comes back |
|---|---|
| "Where in the funnel are we losing the most revenue?" | Target account to first meeting. 1.4 meetings per 100 accounts, against 2.4 in plan. At your average deal size that's about $1.1M of revenue lost a quarter. Most of it is accounts with a new VP Operations heading into peak season. |
| "Why did pipeline drop in September?" | Down $640K. Fewer first meetings explain $410K, mostly in two territories. Smaller partner deals explain $230K. |
| "What did buyers who signed hear that the others didn't?" | Signed accounts heard the peak-season readiness argument (missed deliveries, overtime) on the first call three times as often. Lost accounts mostly heard product features first. |
| "Did the new-VP-Operations play work?" | 3.2 meetings per 100 accounts (42 on 1,300), against 1.4 per 100 (18 on the 1,300 held back at random), same reps, same eight weeks. A gap that size clears chance. Next read in two weeks. |
| "Which deals went quiet after the proposal?" | 14 open deals with no buyer reply in 21 days. Six are over $50K. Here are the owners and the last touch on each. |
What you get
The loss tree
Revenue lost by stage and lever, ranked in dollars, with the stage that binds named.
Driver bridges
When a number moves, the change split into what drove it.
Wins against losses
What separates deals that advanced from those that stalled at one moment.
Best against the rest
What top performers do differently, measured from what they did in your tools.
Program and spend analysis
Which channels, accounts and campaigns produce pipeline, and what each costs.
Briefs for each roleIn progress
A weekly read for execs, managers and reps, in Slack or your AI workspace. Being built.
AI workspaceSelf-serve reportingIn progress
Your team asks its own questions on the same definitions. Being built.
From the answer to the play
Part of step 2, Prioritize by revenue impact.
- Step 011
Connect your data
Reads from your warehouse and its definitions file.
- Step 022
This is step 2
Finds and sizes the costliest decision, so the play is picked by revenue.
- Step 033
Ship into the tools your team uses
Answers land in the tools your team already opens.
- Step 044
Keep improving
The play scorecard reads each play against comparison accounts.
Why dashboards haven't told you what to fix
A dashboard
- Reports on what happened, a month late
- Three tools, three meanings of "qualified"
- AI answers that change every time you ask
An analysis
- Says where revenue is lost and what it's worth
- Definitions written once, used everywhere
- Every answer shows its working
Where to start
GTM AI Bootcamp
Every bootcamp starts here, with your data in and the costliest decision found and sized. In the AI operating partnership, it decides what goes to the top of the backlog.
Before you book
Do we need a data warehouse first?
For any question that spans more than one tool, yes. We build both, starting with the tables the first play needs. See GTM data warehouse.
Will this replace our BI tool?
Not necessarily. We can feed the one you have. What changes is that definitions are written down and agents can use them.
How do you find the leak?
We look across the whole journey, first touch to renewal, for where buyers stall and the money is largest. Then we map wins against losses at that moment.
Our last AI reporting tool gave a different answer every time.
Usually because nothing pinned the definitions. Every answer we build reads the same definitions file and shows the tables and filters it used, so two people asking get the same number.
Where's your line stuck?
Find out where your funnel leaks
30 minutes. Bring last quarter's numbers, and we'll show you the first question we'd ask.
Book a call