B2B go to market strategy.
Long cycles, many signatures. B2B revenue systems fail on the same two things: the deal is modelled as one contact when six people decide it, and attribution assumes a cycle shorter than the one you actually have.
One champion, and five people you never met.
The CRM shows a deal with one contact on it. The actual decision involves a champion, an economic buyer, a security reviewer, a procurement lead and someone in finance who has never spoken to you. The record cannot show risk it has no model for.
Single-threaded. Nobody noticed.
B2B — the committeeModelling how B2B actually buys.
The buying committee as data
Roles on the deal, contacts associated with labels, and a single-threading alert when only one person has engaged in three weeks. The best leading churn-of-deal indicator there is.
Account-level pipeline
Companies as the unit of account with contacts and deals beneath, so a target account list is a real list rather than a spreadsheet beside the CRM.
Attribution over a long cycle
Models that cope with an eleven-month cycle, where first touch was a webinar nobody remembers and last touch was a renewal email. Stating the limits is part of the deliverable.
Stage exit criteria
Each stage defined by something observable the buyer did, not by how the rep feels. This is what makes a long-cycle forecast worth reading.
Procurement and security as stages
For enterprise deals these are real stages with real durations. Modelling them is how cycle time becomes predictable rather than mysterious.
Expansion and land-and-expand
The second deal in an account modelled as its own motion, because it converts differently and should not be forecast the same way.
Strategy that ships as a system.
Diagnose
Where revenue actually comes from today, read from the systems rather than from the deck — sources, cycle times, win rates and the segments that quietly carry the number.
Decide
Segment, offer, motion and pricing written as decisions with owners and dates attached, not as a framework with boxes to fill in later.
Instrument
The CRM, the routing, the definitions and the dashboards rebuilt so the plan is measurable the week it launches rather than the quarter after.
Run it with you
We operate the motion alongside your team until the number repeats, then hand it over with the documentation to keep it repeating.
A cycle measured in weeks.
Reporting built on a thirty-day window against a nine-month cycle tells you almost nothing, and tempts teams to optimise for early-stage volume they cannot convert. Cohort the pipeline by entry period and the picture becomes honest, if slower to read.
What people ask before they commit.
Do we need account-based marketing?
If your deals are large and the target list is finite, yes, and it is mostly an operational discipline rather than a software purchase. If you have thousands of small accounts, probably not.
How do we track the buying committee?
Labelled associations between contacts and deals, engagement per contact, and alerting when the thread narrows. It needs reps to record who they met, which is a process habit more than a technical one.
How do we attribute an eleven-month cycle?
With a model that looks at the whole path and states its assumptions, plus cohorting by entry period. Anyone claiming precision here is selling something.
What about intent data?
Useful for prioritising a finite list, weak as a trigger on its own. It works best combined with your own first-party engagement rather than treated as a lead source.
How long does it take?
Eight to fourteen weeks for the system. Reading the results takes at least one full sales cycle, which is the honest part of the answer.
Where people go from here.
Model the committee.
Tell us what you are running
What the system does today, where it breaks, and when it has to work. An engineer reads it — you get an answer inside one business day, not a sequence.