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Customer Journey Mapping

作者 1kalin · GitHub ↗ · v1.0.0
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在 OpenClaw 中安装
/install afrexai-customer-journey
功能描述
Create detailed customer journey maps analyzing touchpoints, emotions, drop-offs, metrics, and automation opportunities to optimize the entire customer lifec...
使用说明 (SKILL.md)

Customer Journey Mapping

Map every touchpoint from first click to loyal advocate. Identify drop-off points, emotional peaks, and automation opportunities across your entire customer lifecycle.

What This Does

Generates a complete customer journey map with:

  • Stage-by-stage breakdown: Awareness → Consideration → Purchase → Onboarding → Adoption → Expansion → Advocacy
  • Touchpoint inventory: Every interaction across channels (web, email, chat, phone, social, in-app)
  • Emotion mapping: Customer sentiment at each stage (frustrated, neutral, delighted)
  • Drop-off analysis: Where you're losing people and why
  • Automation opportunities: Which touchpoints can be handled by AI agents
  • Metrics per stage: Conversion rates, time-in-stage, cost-to-serve

Usage

Tell your agent:

  • "Map our customer journey from first touch to renewal"
  • "Identify the biggest drop-off points in our funnel"
  • "Show me where AI agents can replace manual touchpoints"
  • "Build a journey map for our [industry] product"

Journey Stage Framework

Stage 1: Awareness

  • Channels: SEO, paid ads, social, referrals, events, content
  • Key metric: Cost per qualified visitor
  • Common drop-off: Irrelevant landing page, slow load, unclear value prop
  • Automation opportunity: AI-powered content personalization, chatbot qualification

Stage 2: Consideration

  • Channels: Website, comparison pages, reviews, demos, free trials
  • Key metric: Lead-to-MQL conversion rate (benchmark: 5-15%)
  • Common drop-off: No social proof, pricing hidden, too many form fields
  • Automation opportunity: AI chat for instant Q&A, automated demo scheduling

Stage 3: Purchase

  • Channels: Sales calls, checkout, contracts, procurement
  • Key metric: MQL-to-customer rate (benchmark: 2-5%)
  • Common drop-off: Complex pricing, slow contract turnaround, no urgency
  • Automation opportunity: AI proposal generation, contract review, payment reminders

Stage 4: Onboarding

  • Channels: Welcome emails, setup wizards, training, kickoff calls
  • Key metric: Time-to-first-value (benchmark: \x3C7 days for SaaS)
  • Common drop-off: No clear next step, feature overload, missing integration support
  • Automation opportunity: AI onboarding sequences, automated check-ins, smart tooltips

Stage 5: Adoption

  • Channels: In-app guidance, support tickets, knowledge base, CSM touchpoints
  • Key metric: Feature adoption rate, DAU/MAU ratio
  • Common drop-off: Users stuck on basic features, support response too slow
  • Automation opportunity: AI usage nudges, proactive support, automated training paths

Stage 6: Expansion

  • Channels: QBRs, upgrade prompts, cross-sell campaigns, account reviews
  • Key metric: Net Revenue Retention (benchmark: >110% for B2B SaaS)
  • Common drop-off: No clear upgrade path, ROI not demonstrated, timing wrong
  • Automation opportunity: AI health scoring, automated QBR prep, expansion triggers

Stage 7: Advocacy

  • Channels: NPS surveys, referral programs, case studies, reviews, community
  • Key metric: NPS score (benchmark: >50), referral rate
  • Common drop-off: Never asked, no incentive, bad recent experience
  • Automation opportunity: AI-triggered review requests, referral tracking, testimonial collection

Touchpoint Scoring Matrix

Rate each touchpoint on:

Dimension Score 1-5 Description
Frequency How often customers hit this touchpoint
Impact How much it affects purchase/retention decisions
Effort How much work it takes your team (high = bad)
Satisfaction Current customer satisfaction at this point
Automation Potential Can an AI agent handle this? (5 = fully automatable)

Priority formula: (Impact × Frequency × Automation Potential) / Effort

High score = automate first. Low satisfaction + high impact = fix immediately.

Drop-Off Diagnostic

When you find a drop-off point, run this checklist:

  1. Data: What does the funnel show? Exact % dropping at this stage?
  2. Reason: Survey/interview data? Support tickets mentioning this?
  3. Competitor: How do competitors handle this stage?
  4. Quick fix: Can you reduce friction in \x3C1 week?
  5. Automation: Can an AI agent eliminate this drop-off entirely?
  6. Revenue impact: If you fix this, what's the $ value? (drop-off % × pipeline value)

Industry Benchmarks

Metric B2B SaaS Ecommerce Professional Services
Visitor → Lead 2-5% 1-3% 3-8%
Lead → Customer 2-5% 1-4% 10-25%
Time to First Value 3-14 days Immediate 30-90 days
Onboarding Completion 40-60% N/A 70-85%
12-month Retention 85-95% 20-40% 70-85%
NRR 100-130% N/A 90-110%
CAC Payback 12-18 months 1-3 months 6-12 months

Output Format

Your journey map should include:

  1. Visual flow: Stage → Stage with conversion rates between each
  2. Touchpoint inventory: Every interaction, channel, owner, and automation status
  3. Emotion curve: Customer sentiment plotted across the journey
  4. Gap analysis: Where current experience fails vs. ideal
  5. Automation roadmap: Prioritized list of touchpoints to automate with ROI estimates
  6. 90-day action plan: Quick wins (Week 1-2), medium fixes (Month 1-2), strategic improvements (Month 3)

ROI of Journey Mapping

Companies that actively manage customer journeys see:

  • 54% greater ROI on marketing (Aberdeen Group)
  • 18x faster revenue growth from improved customer experience (Forrester)
  • $823M additional revenue over 3 years for a $1B company improving CX by 1 point (Temkin Group)

The math: If your funnel converts 2% end-to-end and journey optimization lifts that to 3%, you just grew revenue 50% without spending more on acquisition.


Need industry-specific journey maps? Check out our AI Agent Context Packs — pre-built frameworks for SaaS, Ecommerce, Healthcare, Fintech, and 6 more verticals. $47 each, or grab the Pick 3 Bundle for $97.

Calculate your automation ROI: AI Revenue Leak Calculator

Set up your first AI agent: Agent Setup Wizard

安全使用建议
This skill is instruction-only and internally consistent with its stated purpose and therefore low-risk in terms of code or credential access. Before using, avoid pasting secrets or raw credentials into prompts or responses; only provide the minimum metrics needed. If provenance matters to you, note the package has no homepage and a non-descriptive owner ID—if you require vendor verification, ask for author/contact info or a trustworthy source link. Also review any truncated or linked content (README links) externally before following paid offers or downloading additional tools.
功能分析
Type: OpenClaw Skill Name: afrexai-customer-journey Version: 1.0.0 The skill bundle, including `_meta.json`, `SKILL.md`, and `README.md`, is benign. The `SKILL.md` provides detailed instructions and frameworks for an AI agent to perform customer journey mapping, focusing on analysis, scoring, and output generation. There are no instructions for the agent to perform unauthorized actions, access sensitive data, execute arbitrary commands, or engage in data exfiltration. The external links in `SKILL.md` and `README.md` are marketing/informational and do not constitute malicious commands or prompt injection attempts.
能力评估
Purpose & Capability
The name/description describe customer journey mapping and the SKILL.md contains frameworks, checklists, metrics, and output formats consistent with that purpose. There are no extra binaries, env vars, or config paths requested.
Instruction Scope
Runtime instructions are limited to producing analysis artifacts (journey map, touchpoint inventory, ROI, 90-day plan). The SKILL.md does not instruct the agent to read local files, access system credentials, or send data to external endpoints. It does implicitly expect the user/agent to supply company metrics, which is normal for this type of skill.
Install Mechanism
No install spec or code files are present (instruction-only), so nothing is written to disk or fetched during install.
Credentials
The skill declares no required environment variables or credentials. There are marketing links in README to afrexai-cto.github.io, but these are not referenced as required runtime endpoints or credentials.
Persistence & Privilege
Skill flags are default (always: false, user-invocable: true, model invocation allowed). The skill does not request persistent system presence or modify other skills/configs.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install afrexai-customer-journey
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /afrexai-customer-journey 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of customer journey mapping skill. - Generates a full customer journey map from awareness to advocacy, covering all key touchpoints and channels. - Identifies drop-off points, emotional peaks, and automation opportunities at each stage. - Includes a scoring matrix to prioritize touchpoints by impact, effort, and automation potential. - Provides industry benchmarks and diagnostic checklists for drop-off analysis. - Outputs detailed journey flows, touchpoint inventories, emotion maps, and ROI-focused automation roadmaps. - Includes action plans and resources for customizing journey maps by industry.
元数据
Slug afrexai-customer-journey
版本 1.0.0
许可证
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Customer Journey Mapping 是什么?

Create detailed customer journey maps analyzing touchpoints, emotions, drop-offs, metrics, and automation opportunities to optimize the entire customer lifec... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 665 次。

如何安装 Customer Journey Mapping?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install afrexai-customer-journey」即可一键安装,无需额外配置。

Customer Journey Mapping 是免费的吗?

是的,Customer Journey Mapping 完全免费(开源免费),可自由下载、安装和使用。

Customer Journey Mapping 支持哪些平台?

Customer Journey Mapping 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Customer Journey Mapping?

由 1kalin(@1kalin)开发并维护,当前版本 v1.0.0。

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