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Five Dim Customer

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ojiudezue
five-dim-customer

Use when the user needs to define a target customer beyond thin demographic personas. Triggers on phrases like "who is the customer", "define the persona", "target customer", "who are we building for", "ICP", "ideal customer profile", "buyer persona". Implements the 5-Dimension Target Customer framework from Ch 11 of Building Rocketships.

Overview

Publisherojiudezue
Repositoryproductmind-skills
Skill namefive-dim-customer
Stars
81
Forks
18
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by ojiudezue on GitHub. Read the source before you install it.

Installation

Install the Five Dim Customer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ojiudezue/productmind-skills/tree/main/skills/five-dim-customer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ojiudezue/productmind-skills.git /tmp/productmind-skills
mkdir -p .claude/skills
cp -r /tmp/productmind-skills/skills/five-dim-customer .claude/skills/five-dim-customer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Five Dim Customer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Five Dim Customer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Five Dim Customer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Five-Dimension Target Customer

What this does

Runs Ch 11's 5-Dimension Target Customer framework. Returns a customer dossier across Role, Persona, Objectives, Sharp Problems, JTBD + Workflow, plus the value-chain extension (preceding workflow + succeeding workflow). Replaces thin demographic personas with a structured definition that the rest of the agent's skills depend on.

When to use

Trigger when the user:

  • Has only a demographic persona ("VP Engineering, 100-500 employees") and needs a usable target customer
  • Is shipping a new product or feature and needs to anchor it to a specific buyer
  • Has multiple candidate segments and needs to choose one
  • Is writing positioning, pricing, or roadmap and lacks a clear "who"

When NOT to use

  • User already has a defined target customer; jump to sharp-problem-test or aha-mapper
  • User wants to discover the customer from scratch — run customer-discovery-week first to gather the raw material
  • User is segmenting a quantitative cohort for analytics — different problem; this skill builds qualitative dossiers

The 5 dimensions (from Ch 11)

1. Role

Job title plus the organizational position and level of authority. "VP Engineering at a 200-person Series C company" is a role. "VP Engineering" is a label.

2. Persona

Background, experience, what they value, how they think. The behavioral and cognitive layer. Includes anti-persona — what this customer is not.

3. Objectives

What this person is trying to achieve THIS QUARTER and THIS YEAR. Not mission statements — concrete goals tied to their performance review, team's roadmap, or company's stage. Surface 3–5.

4. Sharp Problems

The 1–3 sharp problems THIS role experiences, named in the customer's words, with frequency and intensity. If you cannot name the sharp problems, the role isn't a viable target — back up to customer-discovery-week.

5. JTBD + Workflow

Jobs to be Done + the workflow that produces them. The JTBD frames WHY the customer hires a solution; the workflow shows WHEN and HOW the hiring decision happens. Include:

  • The target workflow your product would replace
  • The preceding workflow that triggers it
  • The succeeding workflow that comes after

The preceding/succeeding extension is what separates this framework from generic persona work. It surfaces the value-chain coupling that makes integrations, distribution, and pricing decisions clear.

The decision rule

A 5-dimension target customer is COMPLETE when:

  • All 5 dimensions are populated with specifics, not generalities
  • The Sharp Problems dimension has at least 1 problem the user could pass to sharp-problem-test
  • The JTBD + Workflow includes both preceding AND succeeding workflows (not just the target one)

Anything less is DRAFT: the dossier exists but key fields are too generic to use downstream.

Refusal mode

If the user provides only a job title and demographics, return DRAFT and name the missing dimensions. Refuse to fill them with plausible- sounding fiction — the agent doesn't have access to the user's customer interviews and must not invent objectives or problems.

If the user provides multiple plausible target customers, pick the one with the sharpest problem and document why the others were deprioritized — don't return a dossier per customer; the skill is about choosing.

Inputs

  • Candidate role / segment (one or several to choose from)
  • Any prior research, interviews, or quotes
  • The product or product idea being built
  • (Optional) constraints — must be enterprise, must be consumer, etc.

Output structure

## 5-dimension verdict: [COMPLETE | DRAFT]

### Role
[Title + organizational position + authority level]

### Persona
[Background + values + thinking style + anti-persona]

### Objectives
- [Quarter / year objective 1]
- [Objective 2]
- [Objective 3]

### Sharp Problems
- [Problem 1 in customer's words + frequency + intensity]
- [Problem 2]

### JTBD + Workflow
- **JTBD**: [the job the customer hires a solution for]
- **Target workflow**: [the workflow your product replaces]
- **Preceding workflow**: [what triggers the target]
- **Succeeding workflow**: [what comes after]

### Coverage gaps
[Specific missing inputs, if any]

### Recommendation
[Concrete next step — typically 'pass Sharp Problem #1 to sharp-problem-test']

### Analogous case from the book
[A named example]

Worked example from the book

Calendly's target — sales rep at mid-market SaaS (Ch 11)

  • Role: Account Executive at a 50–500 employee SaaS company; quota- carrying; owns external pipeline
  • Persona: 3–8 years sales experience; values speed over polish; comfortable with tools but not a tinkerer; anti-persona = inside- sales SDR (doesn't own the meeting)
  • Objectives:
    • Q: hit 110% of quota
    • Y: convert pipeline 5pp faster than last year
  • Sharp Problems:
    • "I lose 2-3 deals a month to scheduling friction" (~weekly, high intensity)
    • "My calendar is held hostage by anyone who can email me a meeting request" (~daily, moderate)
  • JTBD + Workflow:
    • JTBD: "book the meeting before the prospect's interest cools"
    • Target workflow: external meeting scheduling
    • Preceding: cold outreach reply expressing interest
    • Succeeding: CRM update + prep notes

Gotchas

  • "VP Engineering" is not a role; it's a title. Add company stage, team size, what they own, what they don't.
  • Objectives must be time-bound. "Hit quota" isn't an objective; "hit 110% of Q4 quota" is.
  • The succeeding workflow is the most-skipped dimension. It's where integrations, exports, and analytics fit. Don't drop it.
  • Anti-persona is load-bearing. Naming who this is NOT prevents the most common positioning failure: trying to serve everyone.

Anti-patterns to flag

If the user's dossier has any of these, surface them:

  • Only demographics, no behavior or workflow — that's a marketing persona, not a target customer
  • Sharp Problems section is empty — refuse to call the dossier COMPLETE; route to customer-discovery-week
  • Three+ dimensions filled with the founder's guess vs. customer quotes — flag the assumption risk
  • "Our target is everyone" — return DRAFT and require a single primary

Source

Ch 11: The 5-Dimension Target Customer.


About this skill

This skill is part of the ProductMind Skills catalog — open-source product-judgment skills for AI coding agents.

Source: Building Rocketships by Oji and Ezinne Udezue — Chapter 11. This skill applies one named framework from the book. It works standalone in any agent that supports the SKILL.md standard.

Want the orchestrated version? The RocketshipsGPT agent runs all 13 book skills together, with persistent memory, framework-fidelity evals, voice-checked output, and the book's anti-pattern catches built in. → rocketshipsgpt.productmind.co

License: Skill content licensed under CC BY-SA 4.0. Attribution required; derivative works must share alike. See ADR 0005 for rationale.

Skill version: 1.0.0 · Published: 2026-06-05

Frequently asked questions

What does the Five Dim Customer AI skill do?

Use when the user needs to define a target customer beyond thin demographic personas. Triggers on phrases like "who is the customer", "define the persona", "target customer", "who are we building for", "ICP", "ideal customer profile", "buyer persona". Implements the 5-Dimension Target Customer framework from Ch 11 of Building Rocketships.

Why use Five Dim Customer on TypingMind?

Because you install it once and use it with any model. Five Dim Customer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Five Dim Customer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ojiudezue/productmind-skills/tree/main/skills/five-dim-customer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Five Dim Customer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Five Dim Customer?

As many as you like. As long as a model supports skills, you can use Five Dim Customer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Five Dim Customer AI skill free?

It is published on GitHub by ojiudezue. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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