GTM · Phase 02 · Sales Motion

The sales motion
that actually closes.

Most B2B deals die quietly. The motion runs on instinct, and instinct doesn't repeat, compound, or survive the next hire.

21%
Average B2B win rate.
Four in five deals don't close.
70–80%
Of the buyer's journey done before
they talk to your team.
+30%
Faster ramp for every new rep
when a playbook is documented.
The problem

Three gaps.
One broken motion.

The same pattern across every B2B stage: different symptoms, same root cause.

Gap 01
Discovery built for the wrong buyer

Buyers arrive having already done the research. The questions that close deals now are about urgency, decision committee, and gap. Not about finding the pain.

Gap 02
Deals stall with no signal, no system

No stage logic. No defined exit criteria. Opportunities sit in the pipeline long past dead. Nobody knows which deals are actually moving and which are noise.

Gap 03
Losses don't feed back into wins

Tools like Gong and HubSpot AI score deals that already exist. They don't build what those deals run on. Every loss is a wasted lesson until a win/loss system captures it.

What we solve
The underlying sales motion: the system that AI tools score but can't create. Built on your tools, your data, your stage. AI embedded at every step.
01
Discovery Framework
02
Minimum Viable Playbook
03
CRM Stage Logic
04
Win / Loss Analysis
What this looks like

The output.

Discovery framework
Win / loss patterns
Minimum viable playbook
CRM stage logic
TypeThe question
SituationWhere is pipeline coming from today, and who owns it?
ProblemWhat's the single biggest reason deals stall before close?
ImplicationIf this stays unresolved for another quarter, what does that cost you?
GapWhat would have to be true for you to move on this in the next 30 days?
CommitteeWho else needs to say yes, and what's their biggest concern?
Pipeline AI , scores every call against this framework and flags which questions weren't asked
Closed-won , the pattern
Closed-lost , the pattern
Discovery
Champion + committee mapped before demo
Discovery
Single contact. Ghosted after demo.
Urgency
Specific trigger event named by buyer
Urgency
"We're evaluating options." No trigger, no move.
Proposal
ROI built with buyer's own numbers
Proposal
Generic deck sent. Went into committee. Died.
Win/loss AI , updates this taxonomy automatically from every deal outcome
Deal stageEntry criteriaExit criteriaAI layer
DiscoveryPain confirmed. Buyer engaged. First meeting taken.Committee identified. Urgency and timeline stated.Pipeline AI
ProposalBusiness case built with buyer's numbers. Decision timeline confirmed.ROI model shared. Champion briefed for committee.Deal AI
CloseContract sent. Procurement engaged. Signature pending.Signed. Handoff to onboarding confirmed.Forecast AI
Deal AI , scores every deal against these criteria and flags the moment a stage is about to stall
CompanyStageDays stuckHealthAI signal
Acme CorpProposal3● GreenChampion active. Committee meeting confirmed.
Beta SystemsDiscovery14● AmberNo reply in 10 days. Urgency signal weakening.
Gamma LabsProposal28● RedNo decision maker engaged. Committee not mapped.
Delta SaaSClose2● GreenContract reviewed. Procurement loop closed.
Pipeline AI , monitors every deal in real time and surfaces which ones need action today
Your sales motion, diagnosed

Select your stage.
See exactly what's breaking, and what AI fixes.

Every stage has a different leak. The AI intervention is specific to yours.

Four outputs. All built together. Discovery framework, playbook, CRM logic, and win/loss analysis, same day.
Build mine →
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Stage 01
Pre-Seed to Traction
First unassisted deals. Nothing repeatable yet.
Stage 02
Traction to Product Fit
Signal exists. Close rate is inconsistent.
Stage 03
Validation to PMF
Activity up. Revenue not following.
Stage 04
PMF to Scale
PMF confirmed. System needs to scale.
Stage 05
Scale to Leadership
Growth is there. Efficiency is not.
Stage 06
Established to Re-Pivot
Market moved. Motion needs to adapt.
What gets built

Four outputs.
Built from your pipeline.

Output 01

Discovery Framework

Built for the buyer who already knows their pain. Surfaces urgency, decision criteria, and the gap between what they know and what they've decided.

5 questions calibrated to your stage and sector
Objection map from your actual loss patterns
Qualification gate , advance, slow, or cut
Output 02

Minimum Viable Playbook

The shortest documented path from first contact to signed deal. Built from what has already closed. One page. Ready to hand off.

Deal stages with entry and exit criteria
Demo structure and proposal template
Close motion with follow-up cadence logic
Output 03

CRM Stage Logic

Configured to how deals actually move, not the default stages it shipped with. Stalls flagged by AI before they become losses.

Stage definitions wired into HubSpot or equivalent
AI deal health scoring , green / yellow / red
Clean handoff from Phase 01 Lead Gen Engine
Output 04

Win / Loss Analysis

A structured review of your last 5–10 deals. What the pattern says about your real ICP. Losses stop being wasted.

Deal pattern map , what language closes
Loss taxonomy by objection category
AI forecast signal on deal health by stage
How we work

How the engagement
actually works.

01
Map your last deals

We review your last 5–10 deals: won, lost, and stalled. We map where velocity breaks, which questions weren't asked, and which buying roles were never engaged. No prep required from you.

Diagnosis · your data
02
Build the four outputs

Discovery framework calibrated to your buyers. Playbook built from what has already closed. CRM stage logic wired to how deals actually move. Win/loss taxonomy from your real patterns, not a generic template.

Live build · your motion
03
Wire in the AI layer

Win/loss AI updates from every closed deal. Pipeline AI flags stalls before they go cold. Deal AI scores every active opportunity against the playbook. The system improves every time a deal moves.

AI deployment
04
The next deal runs on a system

CRM configured. Discovery framework in your reps' hands. Playbook documented and enforced. From this point, every deal is scored, every stall is flagged, and every loss feeds back into the next win.

Outputs delivered
Common questions
We already have a playbook. Why do we need this?
What if we don't have enough closed deals to analyse?
Does this replace our CRM or sales tools?
Build the motion that repeats.
Four outputs. AI embedded from the start. Works standalone or as part of the full GTM OS.
Book a Call → ← Back to GTM OS