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
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Trigger Terms
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Workflows
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Workflow 1: Generate User Persona
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Workflow 2: Create Journey Map
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Workflow 3: Plan Usability Test
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Workflow 4: Synthesize Research
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Tool Reference
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Quick Reference Tables
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Knowledge Base
Trigger Terms
Use this skill when you need to:
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"create user persona"
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"generate persona from data"
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"build customer journey map"
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"map user journey"
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"plan usability test"
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"design usability study"
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"analyze user research"
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"synthesize interview findings"
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"identify user pain points"
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"define user archetypes"
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"calculate research sample size"
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"create empathy map"
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"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:
Prepare user data
Required format (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"] } ]
Run persona generator
Human-readable output
python scripts/persona_generator.py
JSON output for integration
python scripts/persona_generator.py json
Review generated components
Component What to Check
Archetype Does it match the data patterns?
Demographics Are they derived from actual data?
Goals Are they specific and actionable?
Frustrations Do they include frequency counts?
Design implications Can designers act on these?
Validate persona
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Show to 3-5 real users: "Does this sound like you?"
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Cross-check with support tickets
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Verify against analytics data
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:
Define scope
Element Description
Persona Which user type
Goal What they're trying to achieve
Start Trigger that begins journey
End Success criteria
Timeframe Hours/days/weeks
Gather journey data
Sources:
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User interviews (ask "walk me through...")
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Session recordings
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Analytics (funnel, drop-offs)
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Support tickets
Map the stages
Typical B2B SaaS stages:
Awareness → Evaluation → Onboarding → Adoption → Advocacy
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?
Identify opportunities
Priority Score = Frequency × Severity × Solvability
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:
Define research questions
Transform vague goals into testable questions:
Vague Testable
"Is it easy to use?" "Can users complete checkout in <3 min?"
"Do users like it?" "Will users choose Design A or B?"
"Does it make sense?" "Can users find settings without hints?"
Select method
Method Participants Duration Best For
Moderated remote 5-8 45-60 min Deep insights
Unmoderated remote 10-20 15-20 min Quick validation
Guerrilla 3-5 5-10 min Rapid feedback
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
Define success metrics
Metric Target
Completion rate
80%
Time on task <2× expected
Error rate <15%
Satisfaction
4/5
Prepare moderator guide
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Think-aloud instructions
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Non-leading prompts
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Post-task questions
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:
Code the data
Tag each data point:
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[GOAL]
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What they want to achieve
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[PAIN]
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What frustrates them
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[BEHAVIOR]
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What they actually do
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[CONTEXT]
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When/where they use product
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[QUOTE]
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Direct user words
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)
Calculate segment sizes
Cluster Users % Viability
Power Users 18 36% Primary persona
Business Users 15 30% Primary persona
Casual Users 12 24% Secondary persona
Extract key findings
For each theme:
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Finding statement
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Supporting evidence (quotes, data)
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Frequency (X/Y participants)
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Business impact
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Recommendation
Prioritize opportunities
Factor Score 1-5
Frequency How often does this occur?
Severity How much does it hurt?
Breadth How many users affected?
Solvability Can we fix this?
Reference: See references/persona-methodology.md for analysis framework
Tool Reference
persona_generator.py
Generates data-driven personas from user research data.
Argument Values Default Description
format (none), json (none) Output format
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:
Archetype Signals Design Focus
power_user Daily use, 10+ features Efficiency, customization
casual_user Weekly use, 3-5 features Simplicity, guidance
business_user Work context, team use Collaboration, reporting
mobile_first Mobile primary Touch, offline, speed
Output Components:
Component Description
demographics Age range, location, occupation, tech level
psychographics Motivations, values, attitudes, lifestyle
behaviors Usage patterns, feature preferences
needs_and_goals Primary, secondary, functional, emotional
frustrations Pain points with evidence
scenarios Contextual usage stories
design_implications Actionable recommendations
data_points Sample size, confidence level
Quick Reference Tables
Research Method Selection
Question Type Best Method Sample Size
"What do users do?" Analytics, observation 100+ events
"Why do they do it?" Interviews 8-15 users
"How well can they do it?" Usability test 5-8 users
"What do they prefer?" Survey, A/B test 50+ users
"What do they feel?" Diary study, interviews 10-15 users
Persona Confidence Levels
Sample Size Confidence Use Case
5-10 users Low Exploratory
11-30 users Medium Directional
31+ users High Production
Usability Issue Severity
Severity Definition Action
4 - Critical Prevents task completion Fix immediately
3 - Major Significant difficulty Fix before release
2 - Minor Causes hesitation Fix when possible
1 - Cosmetic Noticed but not problematic Low priority
Interview Question Types
Type Example Use For
Context "Walk me through your typical day" Understanding environment
Behavior "Show me how you do X" Observing actual actions
Goals "What are you trying to achieve?" Uncovering motivations
Pain "What's the hardest part?" Identifying frustrations
Reflection "What would you change?" Generating ideas
Knowledge Base
Detailed reference guides in references/ :
File Content
persona-methodology.md
Validity criteria, data collection, analysis framework
journey-mapping-guide.md
Mapping process, templates, opportunity identification
example-personas.md
3 complete persona examples with data
usability-testing-frameworks.md
Test planning, task design, analysis
Validation Checklist
Persona Quality
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Based on 20+ users (minimum)
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At least 2 data sources (quant + qual)
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Specific, actionable goals
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Frustrations include frequency counts
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Design implications are specific
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Confidence level stated
Journey Map Quality
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Scope clearly defined (persona, goal, timeframe)
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Based on real user data, not assumptions
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All layers filled (actions, touchpoints, emotions)
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Pain points identified per stage
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Opportunities prioritized
Usability Test Quality
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Research questions are testable
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Tasks are realistic scenarios, not instructions
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5+ participants per design
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Success metrics defined
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Findings include severity ratings
Research Synthesis Quality
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Data coded consistently
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Patterns based on 3+ data points
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Findings include evidence
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Recommendations are actionable
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Priorities justified