Customer Journey Mapping

Create detailed customer journey maps analyzing touchpoints, emotions, drop-offs, metrics, and automation opportunities to optimize the entire customer lifec...

Security Scan

Instruction-only skill that matches its stated purpose (customer journey mapping), requests no credentials or installs, and contains no code or surprising runtime instructions.

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.

Assessment

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.

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:

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 <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

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.

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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

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