Map every touchpoint from first click to loyal advocate. Identify
BY modbenderUPDATED Oct 28, 2026
INTENDED FOR✳Claude Code>_Codex◈OpenClaw↗CursorInstall in a listed agent.
instructions.md
---
name: customer-journey-mapping
description: Map every touchpoint from first click to loyal advocate. Identify
drop-off points, emotional peaks, and automation opportunities across your
entire customer lifecycle.
---
# 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:
| 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.
---
**Need industry-specific journey maps?** Check out our [AI Agent Context Packs](https://afrexai-cto.github.io/context-packs/) — pre-built frameworks for SaaS, Ecommerce, Healthcare, Fintech, and 6 more verticals. $47 each, or grab the [Pick 3 Bundle for $97](https://buy.stripe.com).
**Calculate your automation ROI**: [AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/)
**Set up your first AI agent**: [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/)
---
name: customer-journey-mapping
description: Map every touchpoint from first click to loyal advocate. Identify
drop-off points, emotional peaks, and automation opportunities across your
entire customer lifecycle.
---
# 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:
| 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.
---
**Need industry-specific journey maps?** Check out our [AI Agent Context Packs](https://afrexai-cto.github.io/context-packs/) — pre-built frameworks for SaaS, Ecommerce, Healthcare, Fintech, and 6 more verticals. $47 each, or grab the [Pick 3 Bundle for $97](https://buy.stripe.com).
**Calculate your automation ROI**: [AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/)
**Set up your first AI agent**: [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/)
COMPATIBILITY & REFERENCES
Platform guidance
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.
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