---
type: method
slug: customer-segmentation
title: "Segment your customers"
category: "Business Strategy & Planning"
subcategory: "Market & industry research"
level: intermediate
source: https://deepstoryresearch.com/method/customer-segmentation
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
- Your marketing speaks to "everyone" and converts no one.
- You have customer data and want to find who is most valuable.

## Prompt

# Segment your customers
Method by Deepstory Research: deepstoryresearch.com/method/customer-segmentation

You are a customer-insights lead. Follow the method below step by step. Goal: Clear, actionable customer segments with size, needs, value and how to reach each.

## My inputs
- Business: [BUSINESS]  (example: online furniture store)
- Customer data available: [CUSTOMER_DATA_AVAILABLE]  (example: order history CSV, survey answers)
- Goal: [GOAL]  (example: pick two segments to focus on)

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. If data is attached, profile it first: columns, size, gaps.
2. Propose segmentation bases (needs, behaviour, value, demographics) and pick the most actionable.
3. Define 3–6 segments with a name, description, needs and triggers.
4. Estimate size and value of each; show the method.
5. Score segments on attractiveness and ability to win.
6. Recommend priority segments and the message and channel for each.

## Deliver the output in this structure
- Segmentation approach
- Segment profiles
- Size and value table
- Attractiveness scoring
- Priority segments with message and channel

## Quality rules
- Segments must be mutually exclusive and reachable.
- Do not create segments the data cannot identify.
- 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
- Six-Economy Macro Baseline: https://deepstoryresearch.com/data/global-macro-baseline (AI context file: https://deepstoryresearch.com/context/global-macro-baseline.md)
- E-Commerce Share of US Retail: https://deepstoryresearch.com/data/us-ecommerce-share (AI context file: https://deepstoryresearch.com/context/us-ecommerce-share.md)
- Global EV Adoption: https://deepstoryresearch.com/data/global-ev-adoption (AI context file: https://deepstoryresearch.com/context/global-ev-adoption.md)

---
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.