本文へ移動
cccskills
無料GitHub で公開

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.

インストール方法を見る

含まれるファイル(2)

  • SKILL.md6.7 KB
  • README.md1.2 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

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: <7 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:

DimensionScore 1-5Description
FrequencyHow often customers hit this touchpoint
ImpactHow much it affects purchase/retention decisions
EffortHow much work it takes your team (high = bad)
SatisfactionCurrent customer satisfaction at this point
Automation PotentialCan 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 <1 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

MetricB2B SaaSEcommerceProfessional Services
Visitor → Lead2-5%1-3%3-8%
Lead → Customer2-5%1-4%10-25%
Time to First Value3-14 daysImmediate30-90 days
Onboarding Completion40-60%N/A70-85%
12-month Retention85-95%20-40%70-85%
NRR100-130%N/A90-110%
CAC Payback12-18 months1-3 months6-12 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

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

name: 4d-compression-core version: 1.0.2 description: "把长内容压缩成结构化向量——节省 60-80% Token,保留核心信息" metadata: { "openclaw": { "emoji": "🌀", "requires": { "bins": ["jq", "awk"] }, "triggers": ["压缩", "4d",...

日本語の概要は準備中です。原文の説明を表示しています。

modbender/skill-library-mcp162026年9月28日 更新

Use cheap, TEE-verified AI models from the 0G Compute Network as OpenClaw providers. Discover available models and compare pricing vs OpenRouter, verify provider integrity via hardware attestation (Intel TDX), manage your 0G wallet and sub-accounts, and configure models in OpenClaw with one workflow. Supports DeepSeek, GLM-5, Qwen, and other models available on the 0G marketplace.

日本語の概要は準備中です。原文の説明を表示しています。

modbender/skill-library-mcp162026年9月28日 更新

Send and receive P2P messages using disposable numbers and PINs. No servers, no accounts. Use for human notifications, approval flows, and agent-to-agent communication.

日本語の概要は準備中です。原文の説明を表示しています。

modbender/skill-library-mcp162026年9月28日 更新

0xarchive

無料

Query historical crypto market data from 0xArchive across Hyperliquid, Lighter.xyz, and HIP-3. Covers orderbooks, trades, candles, funding rates, open interest, liquidations, and data quality. Use when the user asks about crypto market data, orderbooks, trades, funding rates, or historical prices on Hyperliquid, Lighter.xyz, or HIP-3.

日本語の概要は準備中です。原文の説明を表示しています。

modbender/skill-library-mcp162026年9月28日 更新

0xwork

無料

Find and complete paid tasks on the 0xWork decentralized marketplace (Base chain, USDC escrow). Use when: the agent wants to earn money/USDC by doing work, discover available tasks, claim a bounty, submit deliverables, check earnings or wallet balance, or set up as a 0xWork worker. Task categories: Writing, Research, Social, Creative, Code, Data. NOT for: posting tasks (use the website), managing the 0xWork platform, or frontend development.

日本語の概要は準備中です。原文の説明を表示しています。

modbender/skill-library-mcp162026年9月28日 更新

Patterns and practices that dramatically accelerate development velocity. Covers parallel execution, automation, feedback loops, workflow optimization, and anti-pattern avoidance. Use when starting projects, planning sprints, optimizing workflows, or onboarding developers.

日本語の概要は準備中です。原文の説明を表示しています。

modbender/skill-library-mcp162026年9月28日 更新

modbender のスキルをすべて見る

このスキルの問題を報告する