customer-journey-map

customer-journey-map is a skill for Claude Code from unixcrh/phuryn-pm-skills. It costs 49 tokens per session (753 once invoked), scanned A, original, MIT.

A customer journey map shows how a specific type of customer experiences a product, from first awareness to recommending it. It records their actions, contact points, feelings, problems, and possible improvements.

In plain words
What is it for?
Use it to improve onboarding, understand customer experience, identify problems, and plan product improvements from research such as interviews, surveys, analytics, or support tickets.
Why use it?
It makes friction and drop-off points visible across the whole experience instead of examining each step separately.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution.

Part of the pm-market-research plugin — 7 skills, 3 commands shipped together

Good fit Use it to improve onboarding, understand customer experience, identify problems, and plan product improvements from research such as interviews, surveys, analytics, or support tickets.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/unixcrh/phuryn-pm-skills/customer-journey-map
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add unixcrh/phuryn-pm-skills --skill customer-journey-map
Clone the repo
git clone --depth 1 https://github.com/unixcrh/phuryn-pm-skills

Made for: Claude Code.

Or install pm-market-research, the plugin that ships this one along with the rest of its 7 skills, 3 commands.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for customer-journey-map

README.md
[![agentmods](https://agentmods.dev/badge/skills/unixcrh/phuryn-pm-skills/customer-journey-map/github.svg)](https://agentmods.dev/skills/unixcrh/phuryn-pm-skills/customer-journey-map)
Your own site
<a href="https://agentmods.dev/skills/unixcrh/phuryn-pm-skills/customer-journey-map"><img src="https://agentmods.dev/badge/skills/unixcrh/phuryn-pm-skills/customer-journey-map/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for customer-journey-map

Your own site · 80×15
<a href="https://agentmods.dev/skills/unixcrh/phuryn-pm-skills/customer-journey-map"><img src="https://agentmods.dev/badge/skills/unixcrh/phuryn-pm-skills/customer-journey-map.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 753 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.00753
Opus 5 $0.00024 $0.00377
Sonnet 5 $0.00010 $0.00151
Haiku 4.5 $0.00005 $0.00075

Measured 12d ago against content hash 656c0e16318b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

customer-journey-map scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

pm-market-research/skills/customer-journey-map/SKILL.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Customer Journey Map

Map the end-to-end customer experience from awareness through advocacy, identifying emotions, pain points, and improvement opportunities at each stage.

Context

You are creating a customer journey map for $ARGUMENTS.

If the user provides files (interview transcripts, survey data, analytics, support tickets, or existing journey maps), read them first. Use web search to understand the product if a URL is provided.

Instructions

  1. Define the persona: Who is traveling this journey? Use a specific persona with JTBD, not a generic user.

  2. Map the journey stages (adapt to the product):

    Stage Description
    Awareness How do they first learn about the product?
    Consideration What do they evaluate? What alternatives do they compare?
    Acquisition How do they sign up or purchase?
    Onboarding First experience with the product — time to value
    Engagement Regular usage — building habits
    Retention What keeps them coming back? What might cause churn?
    Advocacy When and why do they recommend the product to others?
  3. For each stage, document:

    • Touchpoints: Where the user interacts with the product, brand, or team (website, email, in-app, support, social media)
    • User actions: What they do at this stage
    • Thoughts & questions: What's on their mind ("Is this worth my time?" "How do I...?")
    • Emotions: How they feel (excited, confused, frustrated, delighted) — rate on a scale or use emoji indicators
    • Pain points: Friction, confusion, drop-off risks
    • Opportunities: How to improve the experience at this point
  4. Identify critical moments:

    • Aha moment: When the user first experiences core value
    • Moments of truth: Decision points where they commit or abandon
    • Churn triggers: Where users most commonly drop off
  5. Create the journey map table:

    Stage Touchpoint User Action Emotion Pain Point Opportunity

Read the full file on GitHub · 66 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 66 lines · 49 tokens per session scan A 656c0e16318b

Subscribe to this mod's changes

customer-journey-map is a skill published in the GitHub repository unixcrh/phuryn-pm-skills (2 stars, last pushed 6mo ago), licensed MIT. It adds 49 tokens to every session and 753 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens