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Stage hygiene audit: which deals are sitting where they do not belong
The forecast is only as honest as the stage definitions. Audit the pipeline against the exit criteria and find the deals that were promoted on optimism.
The prompt — copy and run it
You are a RevOps analyst auditing pipeline hygiene against stage exit criteria. I will paste the open pipeline and our stage definitions. Produce: A) THE MISPLACEMENT LIST: deals whose recorded evidence does not meet the exit criteria for the stage they sit in, each with the criterion that is unmet, the correct stage on the evidence provided, and the dollar value moving. Where a stage definition I gave you is too vague to test against, say so — that is a finding about the definition, not the deal. B) THE STALE AND STRUCTURAL READ: deals whose age in stage far exceeds my typical cycle, deals with close dates that have already been pushed repeatedly, and deals with no recorded activity in a meaningful window — each with the specific question for the deal owner rather than an automatic downgrade. C) THE FORECAST IMPACT AND THE FIX: what the pipeline looks like after the corrections, the size of the gap this audit just exposed, and the two or three definition or process changes that would stop the same misplacement recurring next quarter. Inputs: [OPEN PIPELINE: INTERNAL DEAL ID, STAGE, AMOUNT, AGE IN STAGE, CLOSE DATE AND ANY PUSHES, LAST ACTIVITY, RECORDED EVIDENCE PER STAGE] · [OUR STAGE DEFINITIONS AND EXIT CRITERIA] · [TYPICAL CYCLE LENGTH BY STAGE] Rules: Do not invent deal facts or probabilities — audit only against the criteria and evidence I provided, and write "insufficient data" where a row is too thin to judge. Flag every proposed recategorisation for the deal owner to confirm; do not treat the audit as the decision. Use internal deal IDs, never customer names, and never include confidential pricing. Keep confidential CRM, deal, and customer data out of consumer AI tools and follow your employer's AI-use policy. This inspects the pipeline; the stage call stays with the deal owner. Verify each flagged deal with its owner before a stage is changed — a hygiene sweep that overwrites the deal owner's judgment destroys the forecast it was meant to fix.
How to use this prompt
- Copy the full prompt above with the Copy button.
- Fill in your inputs. Replace each bracketed placeholder with your specifics:
[OUR STAGE DEFINITIONS AND EXIT CRITERIA][TYPICAL CYCLE LENGTH BY STAGE] - Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.
Why this prompt works
Stage definitions exist in a document and forecasts are built on where deals actually sit, and the distance between the two is the forecast miss nobody can explain in week eleven. Auditing recorded evidence against written exit criteria makes that distance a number, and treating a vague definition as a finding about the definition is what turns a one-off cleanup into a process that stops regenerating the same mess.
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When should I use this prompt?
The forecast is only as honest as the stage definitions. Audit the pipeline against the exit criteria and find the deals that were promoted on optimism.
Why does this prompt work?
Stage definitions exist in a document and forecasts are built on where deals actually sit, and the distance between the two is the forecast miss nobody can explain in week eleven. Auditing recorded evidence against written exit criteria makes that distance a number, and treating a vague definition as a finding about the definition is what turns a one-off cleanup into a process that stops regenerating the same mess.
What mistake does this prompt help you avoid?
Deals promoted on optimism rather than exit criteria — every misplacement cites the unmet criterion and is routed to the deal owner to confirm, never auto-downgraded.
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