UX Researcher Designer
UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use when conducting user research, creating personas, mapping user journeys, planning usability tests, or validating designs.
SkillSpector
LOW
10
0
0
SKILL.md
# 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](#trigger-terms)
- [Workflows](#workflows)
- [Workflow 1: Generate User Persona](#workflow-1-generate-user-persona)
- [Workflow 2: Create Journey Map](#workflow-2-create-journey-map)
- [Workflow 3: Plan Usability Test](#workflow-3-plan-usability-test)
- [Workflow 4: Synthesize Research](#workflow-4-synthesize-research)
- [Tool Reference](#tool-reference)
- [Quick Reference Tables](#quick-reference-tables)
- [Knowledge Base](#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**
| 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
---
### 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
---
### 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
---
### 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
---
## 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
- [ ] 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