UX Researcher & Designer

Generate user personas from research data, create journey maps, plan usability tests, and synthesize research findings into actionable design recommendations.

Table of Contents

• Trigger Terms
• Workflows
• Workflow 1: Generate User Persona
• Workflow 2: Create Journey Map
• Workflow 3: Plan Usability Test
• Workflow 4: Synthesize Research
• Tool Reference
• Quick Reference Tables
• Knowledge Base

Trigger Terms

Use this skill when you need to:

• "create user persona"
• "generate persona from data"
• "build customer journey map"
• "map user journey"
• "plan usability test"
• "design usability study"
• "analyze user research"
• "synthesize interview findings"
• "identify user pain points"
• "define user archetypes"
• "calculate research sample size"
• "create empathy map"
• "identify user needs"

Workflows

Workflow 1: Generate User Persona

Situation: You have user data (analytics, surveys, interviews) and need to create a research-backed persona.

Steps:

1. Prepare user data

Required format (JSON):
json [ { "user_id": "user_1", "age": 32, "usage_frequency": "daily", "features_used": ["dashboard", "reports", "export"], "primary_device": "desktop", "usage_context": "work", "tech_proficiency": 7, "pain_points": ["slow loading", "confusing UI"] } ]

2. Run persona generator
   ```bash
   # Human-readable output
   python scripts/persona_generator.py

# JSON output for integration
python scripts/persona_generator.py json
```

3. Review generated components

4. Validate persona

• Show to 3-5 real users: "Does this sound like you?"
• Cross-check with support tickets
• Verify against analytics data

5. Reference: See references/persona-methodology.md for validity criteria

Workflow 2: Create Journey Map

Situation: You need to visualize the end-to-end user experience for a specific goal.

Steps:

1. Define scope

2. Gather journey data

Sources:
- User interviews (ask "walk me through...")
- Session recordings
- Analytics (funnel, drop-offs)
- Support tickets

3. Map the stages

Typical B2B SaaS stages:
Awareness → Evaluation → Onboarding → Adoption → Advocacy

4. Fill in layers for each stage

Stage: [Name] ├── Actions: What does user do? ├── Touchpoints: Where do they interact? ├── Emotions: How do they feel? (1-5) ├── Pain Points: What frustrates them? └── Opportunities: Where can we improve?

5. Identify opportunities

Priority Score = Frequency × Severity × Solvability

6. Reference: See references/journey-mapping-guide.md for templates

Workflow 3: Plan Usability Test

Situation: You need to validate a design with real users.

Steps:

1. Define research questions

Transform vague goals into testable questions:

2. Select method

3. Design tasks

Good task format:
SCENARIO: "Imagine you're planning a trip to Paris..." GOAL: "Book a hotel for 3 nights in your budget." SUCCESS: "You see the confirmation page."

Task progression: Warm-up → Core → Secondary → Edge case → Free exploration

4. Define success metrics

5. Prepare moderator guide

• Think-aloud instructions
• Non-leading prompts
• Post-task questions

6. Reference: See references/usability-testing-frameworks.md for full guide

Workflow 4: Synthesize Research

Situation: You have raw research data (interviews, surveys, observations) and need actionable insights.

Steps:

1. Code the data

Tag each data point:
- [GOAL] - What they want to achieve
- [PAIN] - What frustrates them
- [BEHAVIOR] - What they actually do
- [CONTEXT] - When/where they use product
- [QUOTE] - Direct user words

2. Cluster similar patterns

```
User A: Uses daily, advanced features, shortcuts
User B: Uses daily, complex workflows, automation
User C: Uses weekly, basic needs, occasional

Cluster 1: A, B (Power Users)
Cluster 2: C (Casual User)
```

3. Calculate segment sizes

4. Extract key findings

For each theme:
- Finding statement
- Supporting evidence (quotes, data)
- Frequency (X/Y participants)
- Business impact
- Recommendation

5. Prioritize opportunities

6. Reference: See references/persona-methodology.md for analysis framework

Tool Reference

persona_generator.py

Generates data-driven personas from user research data.

Sample Output:

============================================================
PERSONA: Alex the Power User
============================================================

📝 A daily user who primarily uses the product for work purposes

Archetype: Power User
Quote: "I need tools that can keep up with my workflow"

👤 Demographics:
  • Age Range: 25-34
  • Location Type: Urban
  • Tech Proficiency: Advanced

🎯 Goals & Needs:
  • Complete tasks efficiently
  • Automate workflows
  • Access advanced features

😤 Frustrations:
  • Slow loading times (14/20 users)
  • No keyboard shortcuts
  • Limited API access

💡 Design Implications:
  → Optimize for speed and efficiency
  → Provide keyboard shortcuts and power features
  → Expose API and automation capabilities

📈 Data: Based on 45 users
    Confidence: High

Archetypes Generated:

Output Components:

Quick Reference Tables

Research Method Selection

Persona Confidence Levels

Usability Issue Severity

Interview Question Types

Knowledge Base

Detailed reference guides in references/:

Validation Checklist

Persona Quality

• [ ] Based on 20+ users (minimum)
• [ ] At least 2 data sources (quant + qual)
• [ ] Specific, actionable goals
• [ ] Frustrations include frequency counts
• [ ] Design implications are specific
• [ ] Confidence level stated

Journey Map Quality

• [ ] Scope clearly defined (persona, goal, timeframe)
• [ ] Based on real user data, not assumptions
• [ ] All layers filled (actions, touchpoints, emotions)
• [ ] Pain points identified per stage
• [ ] Opportunities prioritized

Usability Test Quality

• [ ] Research questions are testable
• [ ] Tasks are realistic scenarios, not instructions
• [ ] 5+ participants per design
• [ ] Success metrics defined
• [ ] Findings include severity ratings

Research Synthesis Quality

• [ ] Data coded consistently
• [ ] Patterns based on 3+ data points
• [ ] Findings include evidence
• [ ] Recommendations are actionable
• [ ] Priorities justified

Related Skills

• UI Design System (product-team/ui-design-system/) — Research findings inform design system decisions
• Product Manager Toolkit (product-team/product-manager-toolkit/) — Customer interview analysis complements persona research

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• 命令和代码默认作为参考；只有用户明确要求执行且目标范围清楚时才可运行。

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