Draft a mutual action plan for a late-stage deal
A mutual action plan (MAP) aligns both sides on steps, owners, and dates before a deal closes—but writing the first draft from scratch is slow. This prompt generates a ready-to-send draft from deal context.
You are a deal strategist. Create a mutual action plan (MAP) for the deal below. The MAP will be sent to the prospect's champion to co-edit before sharing with their leadership.
Deal context:
- Prospect company + champion name/title: {{PROSPECT_AND_CHAMPION}}
- Our product: {{OUR_PRODUCT}}
- Target close date: {{TARGET_CLOSE_DATE}}
- Known remaining steps on prospect's side (e.g., legal review, security questionnaire, budget approval): {{PROSPECT_STEPS}}
- Known remaining steps on our side (e.g., custom demo, procurement paperwork, MSA redline): {{OUR_STEPS}}
- Prospect's go-live deadline or business event driving urgency: {{URGENCY_DRIVER}}
Format the MAP as:
1. A one-sentence shared goal statement both parties can sign off on
2. A table with columns: Step | Owner (Prospect/Us) | Due Date | Status
- Populate with all steps from both sides, sorted by due date
- Leave Status as 'Pending' for all rows
3. A list of 2-3 open questions that need answers before the MAP is finalized
4. A note explaining what happens to the timeline if the go-live deadline is missed
Do not invent steps. If information is missing, insert a [TBD — confirm with champion] placeholder. {{PROSPECT_AND_CHAMPION}}{{OUR_PRODUCT}}{{TARGET_CLOSE_DATE}}{{PROSPECT_STEPS}}{{OUR_STEPS}}{{URGENCY_DRIVER}}
How to use this prompt
- Copy the prompt above (Copy button on the top-right).
- Replace each
{{VAR}}with your own value. Variables:{{PROSPECT_AND_CHAMPION}}{{OUR_PRODUCT}}{{TARGET_CLOSE_DATE}}{{PROSPECT_STEPS}}{{OUR_STEPS}}{{URGENCY_DRIVER}}. - Paste it into one of the recommended tools below.
- Iterate: tighten constraints in the prompt if the output is generic.
Why this prompt is structured this way
The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.
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