---
type: method
slug: cold-outreach-sequence
title: "Write a cold outreach sequence"
category: "Sales"
subcategory: "Prospecting"
level: starter
source: https://deepstoryresearch.com/method/cold-outreach-sequence
publisher: Deepstory Research
---

> **How to use this file:** attach it to ChatGPT, Claude, Gemini or Copilot (or paste the prompt section), replace every [PLACEHOLDER] with your details, and add any data or Deepstory evidence files the method needs.

## When to use this method
- Starting outbound to a new segment.
- Reply rates are below 3%.

## Prompt

# 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.

## Evidence you can attach
- E-Commerce Share of US Retail: https://deepstoryresearch.com/data/us-ecommerce-share (AI context file: https://deepstoryresearch.com/context/us-ecommerce-share.md)
- Six-Economy Macro Baseline: https://deepstoryresearch.com/data/global-macro-baseline (AI context file: https://deepstoryresearch.com/context/global-macro-baseline.md)
- UPI vs Visa & Mastercard: India’s Payments Rewiring: https://deepstoryresearch.com/data/upi-vs-cards (AI context file: https://deepstoryresearch.com/context/upi-vs-cards.md)

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