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Workflow 10 — Deal Execution

Win/Loss Synthesis Engine

Mines every closed deal's transcripts, threads, and timeline into structured cause analysis — then closes the loop by proposing specific positioning, product, and process changes with the evidence attached and minimum-incident thresholds enforced.

At a glance

The Win/Loss Synthesis Engine mines every closed deal's transcripts, threads and timeline into structured cause analysis, then closes the loop by proposing specific positioning, product and process changes with evidence attached and minimum-incident thresholds enforced. It is one of fifteen workflows in the Enterprise GTM Agent Stack, an Opsmarshal series on revenue operations.

Owned by
Product Marketing + RevOps
Writes back to
Insight repo, Change proposals, Audit log
Held to
100% — Closed deals analyzed ≤7 days
Gate
Permission → Evidence → Approval → Audit
Writes to: insight repo + change proposalsApproval: PMM/PM on every proposalThemes: minimum 5 incidents
Business Pain

Why this exists

The status quo

Loss reasons in CRM are a picklist lie — “price” means the rep stopped asking why. Real causes live in transcripts nobody re-reads, so the same losses repeat quarterly with fresh optimism.

What this workflow changes

Each closed deal gets a written cause analysis citing its evidence. Themes only emerge past minimum incident counts, and they arrive as routed proposals: “move security review earlier — 7 of 9 enterprise losses stalled there.”

Architecture

Reference architecture

Inputs
Deal transcripts + threadsfull communications archaeology
CRM timelinestage history, stall points, actors
Stated loss reasonsthe picklist — kept, to measure its divergence from evidence
Agent Layer
Archaeologistper-deal causal analysis with earliest-evidence citations
Pattern Minercross-deal themes with minimum-incident thresholds
Proposal Writerroutes changes to positioning, product, or process owners
Governance
Gate: permission → evidence → approval → auditper-deal analyses reviewable before feeding patterns · no theme below 5 incidents · every proposal approved or rejected with reasons — rejections train the miner
Systems of Record
Insight repodeal analyses + themes, versioned
Change proposalsrouted to owning teams with evidence
Audit logdispositions and their reasons
DecisionChoiceRationale
Deal-level before pattern-levelArchaeology first, themes secondAggregating bad per-deal analysis produces confident nonsense. Each deal's causal story is reviewable on its own before it feeds a pattern.
Minimum-N for themesNo theme ships on fewer than 5 incidentsOne vivid loss shouldn't reshape strategy. Thresholds keep the engine from amplifying anecdotes into initiatives.
Live Demo

Run a scenario through the gate

Three curated scenarios — one that passes, one that flags for a human, one that the gate blocks. Watch the verdict, the evidence rows, and the audit log.

Deal Archaeologist

Governance audit log

[ready] agent idle — pick a scenario
Operator Control Panel

Someone has to run this thing

Agents don't remove operators — they change what operators watch. Console spec: who owns it, what they check, what pages them, and how they pull the plug.

Win/Loss Synthesis Engine — Ops Console

Owner: Product Marketing + RevOps

Daily monitors

  • Analysis backlog — newly closed deals awaiting archaeology

Weekly reviews

  • Theme review — emerging patterns approaching threshold
  • Proposal disposition — accepted/rejected with reasons

Alert thresholds → who gets paged

  • Picklist-vs-evidence divergence >40% → RevOps: the picklist is broken
  • Analysis backlog >7 days → PMM

Manual controls

  • Deal exclusions — legally sensitive losses handled manually
  • Theme threshold config — versioned
  • Kill switch — analysis pauses; no partial themes publish
Eval Metrics

What this workflow is held to

100%
Closed deals analyzed ≤7 days
won and lost — wins hold lessons too
Tracked
Picklist-vs-evidence divergence
how much the official loss reasons lie
%
Proposals actioned
the loop is only closed if changes ship
Failure Modes

How it breaks, and what catches it

Hindsight bias

Analyses narrate inevitability instead of identifying decision points. Mitigation: Every analysis must cite the earliest evidence of the losing factor — the question is “when could we have known,” not “what went wrong.”

Rep defensiveness

Analyses read as blame; reps stop cooperating and the evidence dries up. Mitigation: Process-and-positioning framing in public themes; individual coaching insights route privately to managers only.

Survivor blindness

Only closed deals get mined — but stuck, no-decision deals hold the real lessons. Mitigation: A quarterly no-decision cohort analysis runs alongside win/loss with the same rigor.

Opsmarshal builds workflows like this one inside client stacks — see revenue operations and GTM stack architecture, or book a call to walk through your own.

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