Library/Meeting Prep & Discovery/Qualification Framework Execution/Map Discovery Transcript to MEDDPICC Fields and Gaps
TestedMeeting Prep & DiscoveryQuick Win (under 10 min)

Map Discovery Transcript to MEDDPICC Fields and Gaps

Map transcript evidence to every MEDDPICC field, expose the gaps, and prioritize the next questions.

About this prompt

Turn a discovery transcript into an evidence-linked MEDDPICC assessment that distinguishes confirmed facts, indications, contradictions, and unknowns. Use it after a substantive call to identify qualification gaps and prepare precise follow-up questions without inventing deal intelligence.After a discovery call, this prompt turns [CALL TRANSCRIPT] into an evidence-linked MEDDPICC assessment rather than an unsupported score. It maps transcript passages to each field, labels confirmed, indicated, missing, and conflicting information, and generates focused follow-up questions. Add [DEAL CONTEXT] and [KNOWN CRM DATA] separately so the output can expose contradictions without mixing seller assumptions into buyer evidence. The final CRM draft requires account-owner review before use.

The prompt

You are analyzing a B2B discovery-call transcript to produce an evidence-linked MEDDPICC gap assessment. INPUTS - Call transcript: [CALL TRANSCRIPT] - Optional deal context: [DEAL CONTEXT] - Optional
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Variables to replace

CALL TRANSCRIPT|DEAL CONTEXT|KNOWN CRM DATA

How to run it

  1. Copy the prompt and paste it into Claude, ChatGPT, Gemini, or Copilot — it's tuned to run in any of them.
  2. Replace the variables — swap each bracketed token for your deal's specifics. The variables list above explains every field.
  3. Make it yours — run it, keep what's strong, and tighten your inputs on the next pass. The prompt improves with your context.

What good output looks like

An evidence-linked MEDDPICC table, prioritized gaps and follow-up questions, next actions, and a human-review CRM draft.

Make it yours

Include speaker names and timestamps. Put existing CRM facts in a separate block so the model can identify conflicts between prior data and the call.
StageDiscovery
SeatAE
DifficultyAdvanced
Time to valueQuick Win (under 10 min)
Works withAI-Agnostic
CategoryMeeting Prep & Discovery
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