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

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

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:

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

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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

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

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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:

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Quick Reference Tables

Research Method Selection

Persona Confidence Levels

Usability Issue Severity

Interview Question Types

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Knowledge Base

Detailed reference guides in references/:

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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

UX Research Plan

Study Info

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Research Questions

What do we need to learn? List 3-5 specific, answerable questions.

1. [Primary question - the most important thing to learn] 2. [Secondary question] 3. [Secondary question] 4. [Exploratory question - nice to know] 5. [Exploratory question - nice to know]

What We Already Know

[Summarize existing knowledge, past research, analytics data, assumptions to validate.]

What We Do Not Know

[List specific knowledge gaps this study will address.]

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Methodology

Method: [Usability Testing / User Interviews / Survey / Diary Study / Card Sorting / A/B Test / Contextual Inquiry]

Justification: [Why this method is appropriate for the research questions.]

Approach: [Moderated / Unmoderated / Remote / In-Person]

Duration: [Session length per participant]

Tools: [Platform/tools used - e.g., Lookback, Maze, UserTesting, Zoom]

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Participant Criteria

Target Participants

Screening Questions

1. [Question to verify participant meets criteria] 2. [Question to verify participant meets criteria] 3. [Question to ensure diversity of perspectives]

Exclusion Criteria

• [e.g., Current employees or family of employees]
• [e.g., Participants in a study within the last 6 months]

Sample Size

• Target: [Number] participants
• Justification: [e.g., "5 participants identify ~80% of usability issues" or "Statistical significance requires N=200 for survey"]

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Recruitment Plan

Incentive

• Amount: [$X per session or equivalent]
• Form: [Gift card, account credit, donation to charity]
• Distribution: [Immediately after session / within 5 business days]

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Interview / Test Guide

Introduction (5 minutes)

• Welcome and thank participant
• Explain purpose (learning, not testing them)
• Confirm consent and recording permission
• Set expectations for session duration

Warm-Up Questions (5 minutes)

1. [Background question about their role/context] 2. [Question about current workflow/tools]

Core Tasks / Questions (30-40 minutes)

Task 1: [Description of task or topic area]

• [Specific prompt or scenario]
• [Follow-up probes]

Task 2: [Description of task or topic area]

• [Specific prompt or scenario]
• [Follow-up probes]

Task 3: [Description of task or topic area]

• [Specific prompt or scenario]
• [Follow-up probes]

Wrap-Up (5 minutes)

• Overall impressions
• Anything we did not ask about that they want to share
• Thank participant and explain next steps

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Analysis Framework

Data Collection

• [ ] Session recordings stored securely
• [ ] Notes taken during each session
• [ ] Observations tagged by research question

Analysis Method

• Affinity mapping: Group observations into themes
• Task success rate: [For usability tests] Completion rate per task
• Severity rating: [For issues] Critical / Major / Minor / Cosmetic
• Quantitative analysis: [For surveys] Statistical analysis plan

Synthesis Approach

1. Review all session notes and recordings 2. Identify patterns and themes across participants 3. Map findings to research questions 4. Prioritize findings by impact and frequency 5. Develop actionable recommendations

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Timeline

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Deliverables

• [ ] Research findings report (key insights, evidence, recommendations)
• [ ] Presentation deck for stakeholders
• [ ] Highlight reel of key moments (if recorded)
• [ ] Actionable recommendations prioritized by impact
• [ ] Raw data archive (notes, recordings) stored per data policy

Example Personas

Real output examples showing what good personas look like.

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Table of Contents

• Example 1: Power User Persona
• Example 2: Business User Persona
• Example 3: Casual User Persona
• JSON Output Format
• Quality Checklist

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Example 1: Power User Persona

Script 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
  • Occupation Category: Software Engineer
  • Education Level: Bachelor's degree
  • Tech Proficiency: Advanced

🧠 Psychographics:
  Motivations: Efficiency, Control, Mastery
  Values: Time-saving, Flexibility, Reliability
  Lifestyle: Fast-paced, optimization-focused

🎯 Goals & Needs:
  • Complete tasks efficiently without repetitive work
  • Automate recurring workflows
  • Access advanced features and shortcuts

😤 Frustrations:
  • Slow loading times (mentioned by 14/20 users)
  • No keyboard shortcuts for common actions
  • Limited API access for automation

📊 Behaviors:
  • Frequently uses: Dashboard, Reports, Export, API
  • Usage pattern: 5+ sessions per day
  • Interaction style: Exploratory - uses many features

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

📈 Data: Based on 45 users
    Confidence: High
    Method: Quantitative analysis + 12 qualitative interviews

Data Behind This Persona

Quantitative Data (n=45):

• 78% use product daily
• Average session: 23 minutes
• Average features used: 12
• 84% access via desktop
• Support tickets: 0.2 per month (low)

Qualitative Insights (12 interviews):

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Example 2: Business User Persona

Script Output

============================================================
PERSONA: Taylor the Business Professional
============================================================

📝 A weekly user who primarily uses the product for team collaboration

Archetype: Business User
Quote: "I need to show clear value to my stakeholders"

👤 Demographics:
  • Age Range: 35-44
  • Location Type: Urban/Suburban
  • Occupation Category: Product Manager
  • Education Level: MBA
  • Tech Proficiency: Intermediate

🧠 Psychographics:
  Motivations: Team success, Visibility, Recognition
  Values: Collaboration, Measurable outcomes, Professional growth
  Lifestyle: Meeting-heavy, cross-functional work

🎯 Goals & Needs:
  • Improve team efficiency and coordination
  • Generate reports for stakeholders
  • Integrate with existing work tools (Slack, Jira)

😤 Frustrations:
  • No way to share views with team (11/18 users)
  • Can't generate executive summaries
  • No SSO - team has to manage passwords

📊 Behaviors:
  • Frequently uses: Sharing, Reports, Team Dashboard
  • Usage pattern: 3-4 sessions per week
  • Interaction style: Goal-oriented, feature-specific

💡 Design Implications:
  → Add collaboration and sharing features
  → Build executive reporting and dashboards
  → Integrate with enterprise tools (SSO, Slack)
  → Provide permission and access controls

📈 Data: Based on 38 users
    Confidence: High
    Method: Survey (n=200) + 18 interviews

Data Behind This Persona

Survey Data (n=200):

• 19% of total user base fits this profile
• Average company size: 50-500 employees
• 72% need to share outputs with non-users
• Top request: Team collaboration features

Interview Insights (18 interviews):

Scenario: Quarterly Review Prep

Context: End of quarter, needs to present metrics to leadership
Goal: Create compelling data story in 30 minutes
Current Journey:
  1. Export raw data (works)
  2. Open Excel, make charts (manual)
  3. Copy to PowerPoint (manual)
  4. Share with team for feedback (via email)

Pain Points:
  • No built-in presentation view
  • Charts don't match brand guidelines
  • Can't collaborate on narrative

Opportunity:
  • One-click executive summary
  • Brand-compliant templates
  • In-app commenting on reports

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Example 3: Casual User Persona

Script Output

============================================================
PERSONA: Casey the Casual User
============================================================

📝 A monthly user who uses the product for occasional personal tasks

Archetype: Casual User
Quote: "I just want it to work without having to think about it"

👤 Demographics:
  • Age Range: 25-44
  • Location Type: Mixed
  • Occupation Category: Various
  • Education Level: Bachelor's degree
  • Tech Proficiency: Beginner-Intermediate

🧠 Psychographics:
  Motivations: Task completion, Simplicity
  Values: Ease of use, Quick results
  Lifestyle: Busy, product is means to end

🎯 Goals & Needs:
  • Complete specific task quickly
  • Minimal learning curve
  • Don't have to remember how it works between uses

😤 Frustrations:
  • Too many options, don't know where to start (18/25)
  • Forgot how to do X since last time (15/25)
  • Feels like it's designed for experts (12/25)

📊 Behaviors:
  • Frequently uses: 2-3 core features only
  • Usage pattern: 1-2 sessions per month
  • Interaction style: Focused - uses minimal features

💡 Design Implications:
  → Simplify onboarding and main navigation
  → Provide contextual help and reminders
  → Don't require memorization between sessions
  → Progressive disclosure - hide advanced features

📈 Data: Based on 52 users
    Confidence: High
    Method: Analytics analysis + 25 intercept interviews

Data Behind This Persona

Analytics Data (n=1,200 casual segment):

• 65% of users are casual (< 1 session/week)
• Average features used: 2.3
• Return rate after 30 days: 34%
• Session duration: 4.2 minutes

Intercept Interview Insights (25 quick interviews):

Journey: Infrequent Task Completion

Stage 1: Return After Absence
  Action: Opens app, doesn't recognize interface
  Emotion: 😕 Confused
  Thought: "This looks different, where do I start?"

Stage 2: Feature Hunt
  Action: Clicks around looking for needed feature
  Emotion: 😕 Frustrated
  Thought: "I know I did this before..."

Stage 3: Discovery
  Action: Finds feature (or gives up)
  Emotion: 😐 Relief or 😠 Abandonment
  Thought: "Finally!" or "I'll try something else"

Stage 4: Task Completion
  Action: Uses feature, accomplishes goal
  Emotion: 🙂 Satisfied
  Thought: "That worked, hope I remember next time"

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JSON Output Format

persona_generator.py JSON Output

{
  "name": "Alex the Power User",
  "archetype": "power_user",
  "tagline": "A daily user who primarily uses the product for work purposes",
  "demographics": {
    "age_range": "25-34",
    "location_type": "urban",
    "occupation_category": "Software Engineer",
    "education_level": "Bachelor's degree",
    "tech_proficiency": "Advanced"
  },
  "psychographics": {
    "motivations": ["Efficiency", "Control", "Mastery"],
    "values": ["Time-saving", "Flexibility", "Reliability"],
    "attitudes": ["Early adopter", "Optimization-focused"],
    "lifestyle": "Fast-paced, tech-forward"
  },
  "behaviors": {
    "usage_patterns": ["daily: 45 users", "weekly: 8 users"],
    "feature_preferences": ["dashboard", "reports", "export", "api"],
    "interaction_style": "Exploratory - uses many features",
    "learning_preference": "Self-directed, documentation"
  },
  "needs_and_goals": {
    "primary_goals": [
      "Complete tasks efficiently",
      "Automate workflows"
    ],
    "secondary_goals": [
      "Customize workspace",
      "Integrate with other tools"
    ],
    "functional_needs": [
      "Speed and performance",
      "Keyboard shortcuts",
      "API access"
    ],
    "emotional_needs": [
      "Feel in control",
      "Feel productive",
      "Feel like an expert"
    ]
  },
  "frustrations": [
    "Slow loading times",
    "No keyboard shortcuts",
    "Limited API access",
    "Can't customize dashboard",
    "No batch operations"
  ],
  "scenarios": [
    {
      "title": "Bulk Processing",
      "context": "Monday morning, needs to process week's data",
      "goal": "Complete batch operations quickly",
      "steps": ["Import data", "Apply bulk actions", "Export results"],
      "pain_points": ["No keyboard shortcuts", "Slow processing"]
    }
  ],
  "quote": "I need tools that can keep up with my workflow",
  "data_points": {
    "sample_size": 45,
    "confidence_level": "High",
    "last_updated": "2024-01-15",
    "validation_method": "Quantitative analysis + Qualitative interviews"
  },
  "design_implications": [
    "Optimize for speed and efficiency",
    "Provide keyboard shortcuts and power features",
    "Expose API and automation capabilities",
    "Allow UI customization",
    "Support bulk operations"
  ]
}

Using JSON Output

# Generate JSON for integration
python scripts/persona_generator.py json > persona_power_user.json

# Use with other tools
cat persona_power_user.json | jq '.design_implications'

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Quality Checklist

What Makes a Good Persona

Persona Quality Rubric

Score:

• 25-30: Production-ready persona
• 18-24: Needs refinement
• Below 18: Requires more research

Red Flags in Persona Output

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See also: `persona-methodology.md` for creation process

Journey Mapping Guide

Step-by-step reference for creating user journey maps that drive design decisions.

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Table of Contents

• Journey Map Fundamentals
• Mapping Process
• Journey Stages
• Touchpoint Analysis
• Emotion Mapping
• Opportunity Identification
• Templates

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Journey Map Fundamentals

What Is a Journey Map?

A journey map visualizes the end-to-end experience a user has while trying to accomplish a goal with your product or service.

┌─────────────────────────────────────────────────────────────┐
│                    JOURNEY MAP STRUCTURE                    │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  STAGES:    Awareness → Consideration → Acquisition →      │
│             Onboarding → Regular Use → Advocacy            │
│                                                             │
│  LAYERS:    ┌─────────────────────────────────────────┐    │
│             │ Actions: What user does                 │    │
│             ├─────────────────────────────────────────┤    │
│             │ Touchpoints: Where interaction happens  │    │
│             ├─────────────────────────────────────────┤    │
│             │ Emotions: How user feels                │    │
│             ├─────────────────────────────────────────┤    │
│             │ Pain Points: What frustrates            │    │
│             ├─────────────────────────────────────────┤    │
│             │ Opportunities: Where to improve         │    │
│             └─────────────────────────────────────────┘    │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Journey Map Types

When to Create Journey Maps

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Mapping Process

Step 1: Define Scope

Questions to Answer:

• Which persona is this journey for?
• What goal are they trying to achieve?
• Where does the journey start and end?
• What timeframe does it cover?

Scope Template:

Persona: [Name from persona library]
Goal: [Specific outcome they want]
Start: [Trigger that begins journey]
End: [Success criteria or exit point]
Timeframe: [Hours/Days/Weeks]

Example:

Persona: Alex the Power User
Goal: Set up automated weekly reports
Start: Realizes manual reporting is unsustainable
End: First automated report runs successfully
Timeframe: 1-2 days

Step 2: Gather Data

Data Sources for Journey Mapping:

Interview Questions for Journey Mapping:

1. "Walk me through how you first discovered [product]" 2. "What made you decide to try it?" 3. "Describe your first day using it" 4. "What was the hardest part?" 5. "When did you feel confident using it?" 6. "What would you change about that experience?"

Step 3: Map the Stages

Identify Natural Breakpoints:

Look for moments where:

• User's mindset changes
• Channels shift (web → app → email)
• Time passes (hours, days)
• Goals evolve

Stage Validation:

Each stage should have:

• Clear entry criteria
• Distinct user actions
• Measurable outcomes
• Exit to next stage

Step 4: Fill in Layers

For each stage, document:

1. Actions: What does the user do? 2. Touchpoints: Where do they interact? 3. Thoughts: What are they thinking? 4. Emotions: How do they feel? 5. Pain Points: What's frustrating? 6. Opportunities: Where can we improve?

Step 5: Validate and Iterate

Validation Methods:

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Journey Stages

Common B2B SaaS Stages

┌────────────┬────────────┬────────────┬────────────┬────────────┐
│ AWARENESS  │ EVALUATION │ ONBOARDING │ ADOPTION   │ ADVOCACY   │
├────────────┼────────────┼────────────┼────────────┼────────────┤
│ Discovers  │ Compares   │ Signs up   │ Regular    │ Recommends │
│ problem    │ solutions  │ Sets up    │ usage      │ to others  │
│ exists     │            │ First win  │ Integrates │            │
└────────────┴────────────┴────────────┴────────────┴────────────┘

Stage Detail Template

Stage: Onboarding

Substages: 1. Account creation 2. Profile setup 3. First feature use 4. Integration (if applicable) 5. First value moment

B2C vs. B2B Stages

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Touchpoint Analysis

Touchpoint Categories

Touchpoint Mapping Template

Stage: [Name]
Touchpoint: [Where interaction happens]
Channel: [Web/Mobile/Email/Phone/In-person]
Action: [What user does]
Owner: [Team responsible]
Current Experience: [1-5 rating]
Improvement Priority: [High/Medium/Low]

Cross-Channel Consistency

Check for:

• Information consistency across channels
• Seamless handoffs (web → mobile)
• Context preservation (user doesn't repeat info)
• Brand voice alignment

Red Flags:

• User has to re-enter information
• Different answers from different channels
• Can't continue task on different device
• Inconsistent terminology

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Emotion Mapping

Emotion Scale

                    POSITIVE
                       │
        Delighted  ────┤──── 😄 5
        Pleased    ────┤──── 🙂 4
        Neutral    ────┤──── 😐 3
        Frustrated ────┤──── 😕 2
        Angry      ────┤──── 😠 1
                       │
                    NEGATIVE

Emotional Triggers

Emotion Data Sources

Direct Signals:

• Interview quotes: "I felt so relieved when..."
• Survey scores: NPS, CSAT, CES
• Support sentiment: Angry vs. grateful tickets

Inferred Signals:

• Rage clicks (frustration)
• Quick completion (satisfaction)
• Abandonment (frustration or confusion)
• Return visits (interest or necessity)

Emotion Curve Patterns

The Valley of Death:

😄 ─┐
    │     ╱
    │    ╱
😐 ─│───╱────────
    │╲ ╱
    │ ╳  ← Critical drop-off point
😠 ─│╱ ╲─────────
    │
    Onboarding  First Use  Regular

The Aha Moment:

😄 ─┐         ╱──
    │        ╱
    │       ╱
😐 ─│──────╱────── ← Before: neutral
    │     ↑
😠 ─│     Aha!
    │
    Stage 1  Stage 2  Stage 3

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Opportunity Identification

Pain Point Prioritization

Priority Score = (Frequency + Severity + Breadth) × Solvability

Opportunity Types

Opportunity Canvas

┌─────────────────────────────────────────────────────────────┐
│ OPPORTUNITY: [Name]                                         │
├─────────────────────────────────────────────────────────────┤
│ Stage: [Where in journey]                                   │
│ Current Pain: [What's broken]                               │
│ Desired Outcome: [What should happen]                       │
│ Proposed Solution: [How to fix]                             │
│ Success Metric: [How to measure]                            │
│ Effort: [High/Medium/Low]                                   │
│ Impact: [High/Medium/Low]                                   │
│ Priority: [Calculated]                                      │
└─────────────────────────────────────────────────────────────┘

Quick Wins vs. Strategic Bets

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Templates

Basic Journey Map Template

PERSONA: _______________
GOAL: _______________

┌──────────┬──────────┬──────────┬──────────┬──────────┐
│ STAGE 1  │ STAGE 2  │ STAGE 3  │ STAGE 4  │ STAGE 5  │
├──────────┼──────────┼──────────┼──────────┼──────────┤
│ Actions  │          │          │          │          │
│          │          │          │          │          │
├──────────┼──────────┼──────────┼──────────┼──────────┤
│ Touch-   │          │          │          │          │
│ points   │          │          │          │          │
├──────────┼──────────┼──────────┼──────────┼──────────┤
│ Emotions │          │          │          │          │
│ (1-5)    │          │          │          │          │
├──────────┼──────────┼──────────┼──────────┼──────────┤
│ Pain     │          │          │          │          │
│ Points   │          │          │          │          │
├──────────┼──────────┼──────────┼──────────┼──────────┤
│ Opport-  │          │          │          │          │
│ unities  │          │          │          │          │
└──────────┴──────────┴──────────┴──────────┴──────────┘

Detailed Stage Template

STAGE: _______________
DURATION: _______________
ENTRY CRITERIA: _______________
EXIT CRITERIA: _______________

USER ACTIONS:
1. _______________
2. _______________
3. _______________

TOUCHPOINTS:
• Channel: _____ | Owner: _____
• Channel: _____ | Owner: _____

THOUGHTS:
"_______________"
"_______________"

EMOTIONAL STATE: [1-5] ___

PAIN POINTS:
• _______________
• _______________

OPPORTUNITIES:
• _______________
• _______________

METRICS:
• Completion rate: ___%
• Time spent: ___
• Drop-off: ___%

Service Blueprint Extension

Add backstage layers:

┌─────────────────────────────────────────────────────────────┐
│ FRONTSTAGE (User sees)                                      │
├─────────────────────────────────────────────────────────────┤
│ User actions, touchpoints, emotions                         │
├─────────────────────────────────────────────────────────────┤
│ LINE OF VISIBILITY                                          │
├─────────────────────────────────────────────────────────────┤
│ BACKSTAGE (User doesn't see)                                │
├─────────────────────────────────────────────────────────────┤
│ • Employee actions                                          │
│ • Systems/tools used                                        │
│ • Data flows                                                │
├─────────────────────────────────────────────────────────────┤
│ SUPPORT PROCESSES                                           │
├─────────────────────────────────────────────────────────────┤
│ • Backend systems                                           │
│ • Third-party integrations                                  │
│ • Policies/procedures                                       │
└─────────────────────────────────────────────────────────────┘

---

Quick Reference

Journey Mapping Checklist

Preparation:

• [ ] Persona selected
• [ ] Goal defined
• [ ] Scope bounded
• [ ] Data gathered (interviews, analytics)

Mapping:

• [ ] Stages identified
• [ ] Actions documented
• [ ] Touchpoints mapped
• [ ] Emotions captured
• [ ] Pain points identified

Analysis:

• [ ] Opportunities prioritized
• [ ] Quick wins identified
• [ ] Strategic bets proposed
• [ ] Metrics defined

Validation:

• [ ] Team reviewed
• [ ] User validated
• [ ] Data correlated

Common Mistakes

---

See also: `persona-methodology.md` for persona creation

Persona Methodology Guide

Reference for creating research-backed, data-driven user personas.

---

Table of Contents

• What Makes a Valid Persona
• Data Collection Methods
• Analysis Framework
• Persona Components
• Validation Criteria
• Anti-Patterns

---

What Makes a Valid Persona

Research-Backed vs. Assumption-Based

┌─────────────────────────────────────────────────────────────┐
│                    PERSONA VALIDITY SPECTRUM                │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  ASSUMPTION-BASED          HYBRID          RESEARCH-BACKED  │
│  │───────────────────────────────────────────────────────│  │
│  ❌ Invalid               ⚠️ Limited         ✅ Valid        │
│                                                             │
│  • "Our users are..."    • Some interviews   • 20+ users    │
│  • No data               • 5-10 data points  • Quant + Qual │
│  • Team opinions         • Partial patterns  • Validated    │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Minimum Viability Requirements

The Persona Validity Test

A valid persona must pass these checks:

1. Grounded in Data

• Can you point to specific user quotes?
• Can you show behavioral data supporting claims?
• Are demographics from actual user profiles?

2. Represents a Segment

• Does this persona represent 15%+ of your user base?
• Are there other users who fit this pattern?
• Is it a real cluster, not an outlier?

3. Actionable for Design

• Can designers make decisions from this persona?
• Does it reveal unmet needs?
• Does it clarify feature priorities?

---

Data Collection Methods

Quantitative Sources

Qualitative Sources

Data Collection Matrix

                    QUICK              DEEP
                    (1-2 weeks)        (4+ weeks)
                    │                  │
          ┌─────────┼──────────────────┼─────────┐
  QUANT   │ Survey  │                  │ Product │
          │ + CRM   │                  │ Logs +  │
          │         │                  │ A/B     │
          ├─────────┼──────────────────┼─────────┤
  QUAL    │ 5       │                  │ 15+     │
          │ Quick   │                  │ Deep    │
          │ Calls   │                  │ Inter-  │
          │         │                  │ views   │
          └─────────┴──────────────────┴─────────┘

Interview Protocol

Pre-Interview:

• Review user's analytics data
• Note usage patterns to explore
• Prepare open-ended questions

Interview Structure (45-60 min):

1. Context (10 min)

• "Walk me through your typical day"
• "When do you use [product]?"
• "What were you doing before you found us?"

2. Behaviors (15 min)

• "Show me how you use [feature]"
• "What do you do when [scenario]?"
• "What's your workaround for [pain point]?"

3. Goals & Frustrations (15 min)

• "What are you ultimately trying to achieve?"
• "What's the hardest part about [task]?"
• "If you had a magic wand, what would you change?"

4. Reflection (10 min)

• "What would make you recommend us?"
• "What almost made you quit?"
• "What's missing that you need?"

---

Analysis Framework

Pattern Identification

Step 1: Code Data Points

Tag each insight with:

• [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

Step 2: Cluster Similar Patterns

User A: Uses daily, advanced features, keyboard shortcuts
User B: Uses daily, complex workflows, automation
User C: Uses weekly, basic needs, occasional
User D: Uses daily, power features, API access

Cluster 1: A, B, D (Power Users - daily, advanced)
Cluster 2: C (Casual User - weekly, basic)

Step 3: Calculate Cluster Size

Archetype Classification

Confidence Scoring

Calculate confidence based on data quality:

Confidence = (Sample Size Score + Data Quality Score + Consistency Score) / 3

Sample Size Score:
  5-10 users  = 1 (Low)
  11-30 users = 2 (Medium)
  31+ users   = 3 (High)

Data Quality Score:
  Survey only         = 1 (Low)
  Survey + Analytics  = 2 (Medium)
  Quant + Qual + Logs = 3 (High)

Consistency Score:
  Contradicting data = 1 (Low)
  Some alignment     = 2 (Medium)
  Strong alignment   = 3 (High)

---

Persona Components

Required Elements

Optional Enhancements

Component Depth Guide

Demographics (Keep Brief):

❌ Too detailed:
   Age: 34, Lives: Seattle, Education: MBA from Stanford

✅ Right level:
   Age: 30-40, Urban professional, Graduate degree

Goals (Be Specific):

❌ Too vague:
   "Wants to be productive"

✅ Actionable:
   "Needs to process 50+ items daily without repetitive tasks"

Frustrations (Include Evidence):

❌ Generic:
   "Finds the interface confusing"

✅ With evidence:
   "Can't find export function (mentioned by 8/12 users)"

---

Validation Criteria

Internal Validation

Team Check:

• [ ] Does sales recognize this user type?
• [ ] Does support see these pain points?
• [ ] Does product know these workflows?

Data Check:

• [ ] Can we quantify this segment's size?
• [ ] Do behaviors match analytics?
• [ ] Are quotes from real users?

External Validation

User Validation (recommended):

• Show persona to 3-5 users from segment
• Ask: "Does this sound like you?"
• Iterate based on feedback

A/B Design Test:

• Design for persona A vs. persona B
• Test with actual users
• Measure if persona-driven design wins

Red Flags

Watch for these persona validity problems:

---

Anti-Patterns

1. The Elastic Persona

Problem: Persona stretches to include everyone

❌ "Sarah is 25-55, uses mobile and desktop, wants simplicity
    but also advanced features, works alone and in teams..."

Fix: Create separate personas for distinct segments

2. The Demographic Persona

Problem: All demographics, no psychographics

❌ "John is 35, male, $80k income, urban, MBA..."
   (Nothing about goals, frustrations, behaviors)

Fix: Lead with goals and frustrations, add minimal demographics

3. The Ideal User Persona

Problem: Describes who you want, not who you have

❌ "Emma is a passionate advocate who tells everyone
    about our product and uses every feature daily..."

Fix: Base on real user data, include realistic limitations

4. The Committee Persona

Problem: Each stakeholder added their opinions

❌ CEO added "enterprise-focused"
   Sales added "loves demos"
   Support added "never calls support"

Fix: Single owner, data-driven only

5. The Stale Persona

Problem: Created once, never updated

❌ "Last updated: 2019"
   Product has changed completely since then

Fix: Review quarterly, update with new data

---

Quick Reference

Persona Creation Checklist

• [ ] Minimum 20 users in data set
• [ ] At least 2 data sources (quant + qual)
• [ ] Clear segment boundaries
• [ ] Actionable for design decisions
• [ ] Validated with team and users
• [ ] Documented data sources
• [ ] Confidence level stated

Time Investment Guide

---

See also: `example-personas.md` for output examples

Usability Testing Frameworks

Reference for planning and conducting usability tests that produce actionable insights.

---

Table of Contents

• Testing Methods Overview
• Test Planning
• Task Design
• Moderation Techniques
• Analysis Framework
• Reporting Template

---

Testing Methods Overview

Method Selection Matrix

Participant Count Guidelines

┌─────────────────────────────────────────────────────────────┐
│                    FINDING USABILITY ISSUES                 │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  % Issues Found                                             │
│  100% ┤                          ●────●────●                │
│   90% ┤                    ●─────                           │
│   80% ┤              ●─────                                 │
│   75% ┤         ●────                 ← 5 users: 75-80%     │
│   50% ┤    ●────                                            │
│   25% ┤ ●──                                                 │
│    0% ┼────┬────┬────┬────┬────┬────                       │
│        1    2    3    4    5    6+   Users                  │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Nielsen's Rule: 5 users find ~75-80% of usability issues

---

Test Planning

Research Questions

Transform vague goals into testable questions:

Test Plan Template

PROJECT: _______________
DATE: _______________
RESEARCHER: _______________

RESEARCH QUESTIONS:
1. _______________
2. _______________
3. _______________

PARTICIPANTS:
• Target: [Persona or user type]
• Count: [Number]
• Recruitment: [Source]
• Incentive: [Amount/type]

METHOD:
• Type: [Moderated/Unmoderated/Remote/In-person]
• Duration: [Minutes per session]
• Environment: [Tool/Location]

TASKS:
1. [Task description + success criteria]
2. [Task description + success criteria]
3. [Task description + success criteria]

METRICS:
• Completion rate (target: __%)
• Time on task (target: __ min)
• Error rate (target: __%)
• Satisfaction (target: __/5)

SCHEDULE:
• Pilot: [Date]
• Sessions: [Date range]
• Analysis: [Date]
• Report: [Date]

Pilot Testing

Always pilot before real sessions:

• Run 1-2 test sessions with team members
• Check task clarity and timing
• Test recording/screen sharing
• Adjust based on pilot feedback

Pilot Checklist:

• [ ] Tasks understood without clarification
• [ ] Session fits in time slot
• [ ] Recording captures screen + audio
• [ ] Post-test questions make sense

---

Task Design

Good vs. Bad Tasks

Task Construction Formula

SCENARIO + GOAL + SUCCESS CRITERIA

Scenario: Context that makes task realistic
Goal: What user needs to accomplish
Success: How we know they succeeded

Example:
"Imagine you're planning a trip to Paris next month. [SCENARIO]
Book a hotel for 3 nights in your budget. [GOAL]
You've succeeded when you see the confirmation page. [SUCCESS]"

Task Types

Task Difficulty Progression

Start easy, increase difficulty:

Task 1: Warm-up (easy, builds confidence)
Task 2: Core flow (main functionality)
Task 3: Secondary flow (important but less common)
Task 4: Edge case (stress test)
Task 5: Free exploration (open-ended)

---

Moderation Techniques

The Think-Aloud Protocol

Instruction Script: "As you work through the tasks, please think out loud. Tell me what you're looking at, what you're thinking, and what you're trying to do. There are no wrong answers - we're testing the design, not you."

Prompts When Silent:

• "What are you thinking right now?"
• "What do you expect to happen?"
• "What are you looking for?"
• "Tell me more about that"

Handling Common Situations

Non-Leading Question Techniques

Post-Task Questions

After each task: 1. "How difficult was that?" (1-5 scale) 2. "What, if anything, was confusing?" 3. "What would you improve?"

After all tasks: 1. "What stood out to you?" 2. "What was the best/worst part?" 3. "Would you use this? Why/why not?"

---

Analysis Framework

Severity Rating Scale

Issue Documentation Template

ISSUE ID: ___
SEVERITY: [1-4]
FREQUENCY: [X/Y participants]

TASK: [Which task]
TIMESTAMP: [When in session]

OBSERVATION:
[What happened - factual description]

USER QUOTE:
"[Direct quote if available]"

HYPOTHESIS:
[Why this might be happening]

RECOMMENDATION:
[Proposed solution]

AFFECTED PERSONA:
[Which user types]

Pattern Recognition

Quantitative Signals:

• Task completion rate < 80%
• Time on task > 2x expected
• Error rate > 20%
• Satisfaction < 3/5

Qualitative Signals:

• Same confusion point across 3+ users
• Repeated verbal frustration
• Workaround attempts
• Feature requests during task

Analysis Matrix

┌─────────────────┬───────────┬───────────┬───────────┐
│ Issue           │ Frequency │ Severity  │ Priority  │
├─────────────────┼───────────┼───────────┼───────────┤
│ Can't find X    │ 4/5       │ Critical  │ HIGH      │
│ Confusing label │ 3/5       │ Major     │ HIGH      │
│ Slow loading    │ 2/5       │ Minor     │ MEDIUM    │
│ Typo in text    │ 1/5       │ Cosmetic  │ LOW       │
└─────────────────┴───────────┴───────────┴───────────┘

Priority = Frequency × Severity

---

Reporting Template

Executive Summary

USABILITY TEST REPORT
[Project Name] | [Date]

OVERVIEW
• Participants: [N] users matching [persona]
• Method: [Type of test]
• Tasks: [N] tasks covering [scope]

KEY FINDINGS
1. [Most critical issue + impact]
2. [Second issue]
3. [Third issue]

SUCCESS METRICS
• Completion rate: [X]% (target: Y%)
• Avg. time on task: [X] min (target: Y min)
• Satisfaction: [X]/5 (target: Y/5)

TOP RECOMMENDATIONS
1. [Highest priority fix]
2. [Second priority]
3. [Third priority]

Detailed Findings Section

FINDING 1: [Title]

Severity: [Critical/Major/Minor/Cosmetic]
Frequency: [X/Y participants]
Affected Tasks: [List]

What Happened:
[Description of the problem]

Evidence:
• P1: "[Quote]"
• P3: "[Quote]"
• [Video timestamp if available]

Impact:
[How this affects users and business]

Recommendation:
[Proposed solution with rationale]

Design Mockup:
[Optional: before/after if applicable]

Metrics Dashboard

TASK PERFORMANCE SUMMARY

Task 1: [Name]
├─ Completion: ████████░░ 80%
├─ Avg. Time: 2:15 (target: 2:00)
├─ Errors: 1.2 avg
└─ Satisfaction: ★★★★☆ 4.2/5

Task 2: [Name]
├─ Completion: ██████░░░░ 60% ⚠️
├─ Avg. Time: 4:30 (target: 3:00) ⚠️
├─ Errors: 3.1 avg ⚠️
└─ Satisfaction: ★★★☆☆ 3.1/5

[Continue for all tasks]

---

Quick Reference

Session Checklist

Before Session:

• [ ] Test plan finalized
• [ ] Tasks written and piloted
• [ ] Recording set up and tested
• [ ] Consent form ready
• [ ] Prototype/product accessible
• [ ] Note-taking template ready

During Session:

• [ ] Consent obtained
• [ ] Think-aloud explained
• [ ] Recording started
• [ ] Tasks presented one at a time
• [ ] Post-task ratings collected
• [ ] Debrief questions asked
• [ ] Thanks and incentive

After Session:

• [ ] Notes organized
• [ ] Recording saved
• [ ] Initial impressions captured
• [ ] Issues logged

Common Metrics

---

See also: `journey-mapping-guide.md` for contextual research