PlaybookPrompts

Craft a reengagement message for a deal lost 6 months ago

Sales & Outreach reengagementpipelineoutreach

Deals lost to 'no decision' or a competitor often reopen within 6–18 months when circumstances change. This prompt writes a reengagement message calibrated to what has changed—on their side or yours—since the deal went cold.

Prompt
You are a senior sales rep. Write a reengagement message for a deal that was lost or stalled at least 3 months ago.

Context:
- Prospect's name and title: {{PROSPECT_NAME_TITLE}}
- Company name: {{COMPANY_NAME}}
- Why the deal was lost or stalled (be specific): {{LOSS_REASON}}
- What has changed since then — pick one or more:
  a) On our side (new feature, pricing change, case study): {{OUR_CHANGE}}
  b) On their side (new job posting, funding round, leadership change, news): {{THEIR_CHANGE}}
- Our product: {{OUR_PRODUCT}}

Produce:
1. A subject line that does not say 'Checking in' or 'Circling back'
2. A message body (under 90 words) structured as:
   - One sentence acknowledging the prior conversation without relitigating it
   - One sentence on what specifically changed (use {{OUR_CHANGE}} or {{THEIR_CHANGE}}, not both unless they connect naturally)
   - One sentence explaining why that change makes now a different conversation
   - A soft call to action with a specific date window
3. A note on which loss reason types make reengagement unlikely regardless of what changed (e.g., lost to a multi-year contract they just signed)
Variables to fill in
  • {{PROSPECT_NAME_TITLE}}
  • {{COMPANY_NAME}}
  • {{LOSS_REASON}}
  • {{OUR_CHANGE}}
  • {{THEIR_CHANGE}}
  • {{OUR_PRODUCT}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{PROSPECT_NAME_TITLE}}{{COMPANY_NAME}}{{LOSS_REASON}}{{OUR_CHANGE}}{{THEIR_CHANGE}}{{OUR_PRODUCT}}.
  3. Paste it into one of the recommended tools below.
  4. 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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