PlaybookPrompts

Write a voicemail script for a cold call that prompts callbacks

Sales & Outreach cold-callingoutreachprospecting

Most cold voicemails are either too long or too vague to act on. This prompt builds a tight, curiosity-driven voicemail under 25 seconds that gives the prospect a concrete reason to call back.

Prompt
You are a cold calling coach. Write a voicemail script I can leave for a prospect I've never spoken to.

Requirements:
1. The script must be speakable in 20-25 seconds at a natural pace — count words accordingly (roughly 70-80 words max).
2. Open with your name and company in the first five words — don't bury it.
3. Include one specific, concrete hook tied to something relevant to the prospect's role or company (use the context I give you). Do not use a generic value statement.
4. State a single clear next step — what you want them to do and the phone number to call back. Do not give multiple options.
5. End with your name again.
6. Write three versions: one that leads with a pain signal, one that leads with a peer reference (e.g., 'I work with a lot of [persona] at [similar companies]'), and one that leads with a specific trigger event.
7. Flag which version is weakest given the context I've provided and why.

Prospect name and title: {{PROSPECT_NAME_TITLE}}
Company name: {{COMPANY_NAME}}
Relevant context or trigger: {{OUTREACH_CONTEXT}}
Your name, company, and callback number: {{SENDER_INFO}}

If you have no trigger event or context, version three will be generic — skip it and note that.
Variables to fill in
  • {{PROSPECT_NAME_TITLE}}
  • {{COMPANY_NAME}}
  • {{OUTREACH_CONTEXT}}
  • {{SENDER_INFO}}

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}}{{OUTREACH_CONTEXT}}{{SENDER_INFO}}.
  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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