neekware/artifacts/bundle/skills/product-team/ux-researcher-designer

UX Researcher & Designer

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

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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

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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"

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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):

   [
     {
       "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

   # Human-readable output
   python scripts/persona_generator.py
   
   # JSON output for integration
   python scripts/persona_generator.py json
   

3. 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? |

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

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Workflow 2: Create Journey Map

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

Steps:

1. 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 |

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

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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:

   | 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?" |

2. 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 |

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

   | Metric | Target | | --------------- | ------------ | | Completion rate | >80% | | Time on task | <2× expected | | Error rate | <15% | | Satisfaction | >4/5 |

5. Prepare moderator guide

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

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

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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

   | Cluster | Users | % | Viability | | -------------- | ----- | --- | ----------------- | | Power Users | 18 | 36% | Primary persona | | Business Users | 15 | 30% | Primary persona | | Casual Users | 12 | 24% | Secondary persona |

4. Extract key findings

   For each theme:

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

5. 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? |

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

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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 |

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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 |

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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 |

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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

Creator: Product Team License: MIT Source Repo: neekware/ehaye-skills Source Bucket: product-team Original Path: product-team/ux-researcher-designer