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ux-researcher-designer

UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey.

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Installation

npx clawhub@latest install ux-researcher-designer

View the full skill documentation and source below.

Documentation

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

- Workflow 1: Generate User Persona - Workflow 2: Create Journey Map - Workflow 3: Plan Usability Test - Workflow 4: Synthesize Research

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:

  • 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
  • - Show to 3-5 real users: "Does this sound like you?"
    - Cross-check with support tickets
    - 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:
    - User interviews (ask "walk me through...")
    - Session recordings
    - Analytics (funnel, drop-offs)
    - 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
  • - Think-aloud instructions
    - Non-leading prompts
    - 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:
    - [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

  • 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:
    - Finding statement
    - Supporting evidence (quotes, data)
    - Frequency (X/Y participants)
    - Business impact
    - 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.

    ArgumentValuesDefaultDescription
    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:

    ArchetypeSignalsDesign Focus
    power_userDaily use, 10+ featuresEfficiency, customization
    casual_userWeekly use, 3-5 featuresSimplicity, guidance
    business_userWork context, team useCollaboration, reporting
    mobile_firstMobile primaryTouch, offline, speed
    Output Components:
    ComponentDescription
    demographicsAge range, location, occupation, tech level
    psychographicsMotivations, values, attitudes, lifestyle
    behaviorsUsage patterns, feature preferences
    needs_and_goalsPrimary, secondary, functional, emotional
    frustrationsPain points with evidence
    scenariosContextual usage stories
    design_implicationsActionable recommendations
    data_pointsSample size, confidence level

    Quick Reference Tables

    Research Method Selection

    Question TypeBest MethodSample Size
    "What do users do?"Analytics, observation100+ events
    "Why do they do it?"Interviews8-15 users
    "How well can they do it?"Usability test5-8 users
    "What do they prefer?"Survey, A/B test50+ users
    "What do they feel?"Diary study, interviews10-15 users

    Persona Confidence Levels

    Sample SizeConfidenceUse Case
    5-10 usersLowExploratory
    11-30 usersMediumDirectional
    31+ usersHighProduction

    Usability Issue Severity

    SeverityDefinitionAction
    4 - CriticalPrevents task completionFix immediately
    3 - MajorSignificant difficultyFix before release
    2 - MinorCauses hesitationFix when possible
    1 - CosmeticNoticed but not problematicLow priority

    Interview Question Types

    TypeExampleUse 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/:

    FileContent
    persona-methodology.mdValidity criteria, data collection, analysis framework
    journey-mapping-guide.mdMapping process, templates, opportunity identification
    example-personas.md3 complete persona examples with data
    usability-testing-frameworks.mdTest planning, task design, analysis

    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