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MethodSalesProspectingStarter

Write a cold outreach sequence

A personalised multi-touch email and LinkedIn sequence that earns replies without spam tactics.

This is a practical, copy-paste process for starting outbound to a new segment.. Use it when you want a clear structure, then add your own details and the linked evidence.

Published by Deepstory Research. Reviewed Sep 2026.

How to use this method

  1. 1. Copy or downloadCopy the prompt below, or download the method file and attach it to your chat.
  2. 2. Paste into any AIChatGPT, Claude, Gemini or Copilot. Replace each [PLACEHOLDER] with your details, or let the AI ask you.
  3. 3. Add evidenceAttach the evidence files listed on this page so the AI works from sourced numbers, not guesses.

The prompt

Paste it as-is. The AI will ask for anything still in [BRACKETS].

Download .md
# Write a cold outreach sequence
Method by Deepstory Research: deepstoryresearch.com/method/cold-outreach-sequence

You are a top-performing SDR manager. Follow the method below step by step. Goal: A personalised multi-touch email and LinkedIn sequence that earns replies without spam tactics.

## My inputs
- Your offer: [YOUR_OFFER]  (example: BIM coordination services)
- Target persona: [TARGET_PERSONA]  (example: project directors at contractors)
- Proof point: [PROOF_POINT]  (example: cut clash rework 30% for a client)
- Channels: [CHANNELS]  (example: email + LinkedIn)
- Prospect research: [PROSPECT_RESEARCH]  (example: paste notes if you have them)

Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source.

## Steps to follow
1. Define the trigger or reason to reach out now.
2. Write a 4–6 touch sequence with timing and channel.
3. Keep first email under 90 words with one clear ask.
4. Add personalisation slots and example lines.
5. Write a breakup message.
6. Give A/B subject lines.

## Deliver the output in this structure
- Sequence timeline
- Messages
- Personalisation guide
- Subject-line tests

## Quality rules
- Comply with anti-spam law: identify sender, easy opt-out.
- No fake "Re:" subjects or false familiarity.
- Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION.
- If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED].
- End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.

What you need to give the AI

InputPlaceholderExample
Your offer[YOUR_OFFER]BIM coordination services
Target persona[TARGET_PERSONA]project directors at contractors
Proof point[PROOF_POINT]cut clash rework 30% for a client
Channels[CHANNELS]email + LinkedIn
Prospect research[PROSPECT_RESEARCH]paste notes if you have them

Use it when

  • Starting outbound to a new segment.
  • Reply rates are below 3%.

What you get

  • Sequence timeline
  • Messages
  • Personalisation guide
  • Subject-line tests

The procedure, step by step

Read this before you run it, so you can check the AI actually followed the method.

  1. 1

    Define the trigger or reason to reach out now.

  2. 2

    Write a 4–6 touch sequence with timing and channel.

  3. 3

    Keep first email under 90 words with one clear ask.

  4. 4

    Add personalisation slots and example lines.

  5. 5

    Write a breakup message.

  6. 6

    Give A/B subject lines.

Quality checks built into the prompt

  • • Comply with anti-spam law: identify sender, easy opt-out.
  • • No fake "Re:" subjects or false familiarity.
  • • Every number labelled FACT, ESTIMATE or ASSUMPTION; claims outside attached evidence tagged [UNVERIFIED].

Evidence to use with this method

Methods tell the AI how to think. Evidence gives it sourced numbers to think with. Download a context file and attach it with the prompt.

Run next

Methods that chain well after this one.

Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment decisions need a qualified professional.