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.

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ux-researcher-designerUX 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.

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

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):

    [
      {
        "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


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
  • 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
1---
2name: "ux-researcher-designer"
3description: 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.
4---
5 
6# UX Researcher & Designer
7 
8Generate user personas from research data, create journey maps, plan usability tests, and synthesize research findings into actionable design recommendations.
9 
10---
11 
12## Table of Contents
13 
14- [Trigger Terms](#trigger-terms)
15- [Workflows](#workflows)
16 - [Workflow 1: Generate User Persona](#workflow-1-generate-user-persona)
17 - [Workflow 2: Create Journey Map](#workflow-2-create-journey-map)
18 - [Workflow 3: Plan Usability Test](#workflow-3-plan-usability-test)
19 - [Workflow 4: Synthesize Research](#workflow-4-synthesize-research)
20- [Tool Reference](#tool-reference)
21- [Quick Reference Tables](#quick-reference-tables)
22- [Knowledge Base](#knowledge-base)
23 
24---
25 
26## Trigger Terms
27 
28Use this skill when you need to:
29 
30- "create user persona"
31- "generate persona from data"
32- "build customer journey map"
33- "map user journey"
34- "plan usability test"
35- "design usability study"
36- "analyze user research"
37- "synthesize interview findings"
38- "identify user pain points"
39- "define user archetypes"
40- "calculate research sample size"
41- "create empathy map"
42- "identify user needs"
43 
44---
45 
46## Workflows
47 
48### Workflow 1: Generate User Persona
49 
50**Situation:** You have user data (analytics, surveys, interviews) and need to create a research-backed persona.
51 
52**Steps:**
53 
541. **Prepare user data**
55 
56 Required format (JSON):
57 ```json
58 [
59 {
60 "user_id": "user_1",
61 "age": 32,
62 "usage_frequency": "daily",
63 "features_used": ["dashboard", "reports", "export"],
64 "primary_device": "desktop",
65 "usage_context": "work",
66 "tech_proficiency": 7,
67 "pain_points": ["slow loading", "confusing UI"]
68 }
69 ]
70 ```
71 
722. **Run persona generator**
73 ```bash
74 # Human-readable output
75 python scripts/persona_generator.py
76 
77 # JSON output for integration
78 python scripts/persona_generator.py json
79 ```
80 
813. **Review generated components**
82 
83 | Component | What to Check |
84 |-----------|---------------|
85 | Archetype | Does it match the data patterns? |
86 | Demographics | Are they derived from actual data? |
87 | Goals | Are they specific and actionable? |
88 | Frustrations | Do they include frequency counts? |
89 | Design implications | Can designers act on these? |
90 
914. **Validate persona**
92 
93 - Show to 3-5 real users: "Does this sound like you?"
94 - Cross-check with support tickets
95 - Verify against analytics data
96 
975. **Reference:** See `references/persona-methodology.md` for validity criteria
98 
99---
100 
101### Workflow 2: Create Journey Map
102 
103**Situation:** You need to visualize the end-to-end user experience for a specific goal.
104 
105**Steps:**
106 
1071. **Define scope**
108 
109 | Element | Description |
110 |---------|-------------|
111 | Persona | Which user type |
112 | Goal | What they're trying to achieve |
113 | Start | Trigger that begins journey |
114 | End | Success criteria |
115 | Timeframe | Hours/days/weeks |
116 
1172. **Gather journey data**
118 
119 Sources:
120 - User interviews (ask "walk me through...")
121 - Session recordings
122 - Analytics (funnel, drop-offs)
123 - Support tickets
124 
1253. **Map the stages**
126 
127 Typical B2B SaaS stages:
128 ```
129 Awareness → Evaluation → Onboarding → Adoption → Advocacy
130 ```
131 
1324. **Fill in layers for each stage**
133 
134 ```
135 Stage: [Name]
136 ├── Actions: What does user do?
137 ├── Touchpoints: Where do they interact?
138 ├── Emotions: How do they feel? (1-5)
139 ├── Pain Points: What frustrates them?
140 └── Opportunities: Where can we improve?
141 ```
142 
1435. **Identify opportunities**
144 
145 Priority Score = Frequency × Severity × Solvability
146 
1476. **Reference:** See `references/journey-mapping-guide.md` for templates
148 
149---
150 
151### Workflow 3: Plan Usability Test
152 
153**Situation:** You need to validate a design with real users.
154 
155**Steps:**
156 
1571. **Define research questions**
158 
159 Transform vague goals into testable questions:
160 
161 | Vague | Testable |
162 |-------|----------|
163 | "Is it easy to use?" | "Can users complete checkout in <3 min?" |
164 | "Do users like it?" | "Will users choose Design A or B?" |
165 | "Does it make sense?" | "Can users find settings without hints?" |
166 
1672. **Select method**
168 
169 | Method | Participants | Duration | Best For |
170 |--------|--------------|----------|----------|
171 | Moderated remote | 5-8 | 45-60 min | Deep insights |
172 | Unmoderated remote | 10-20 | 15-20 min | Quick validation |
173 | Guerrilla | 3-5 | 5-10 min | Rapid feedback |
174 
1753. **Design tasks**
176 
177 Good task format:
178 ```
179 SCENARIO: "Imagine you're planning a trip to Paris..."
180 GOAL: "Book a hotel for 3 nights in your budget."
181 SUCCESS: "You see the confirmation page."
182 ```
183 
184 Task progression: Warm-up → Core → Secondary → Edge case → Free exploration
185 
1864. **Define success metrics**
187 
188 | Metric | Target |
189 |--------|--------|
190 | Completion rate | >80% |
191 | Time on task | <2× expected |
192 | Error rate | <15% |
193 | Satisfaction | >4/5 |
194 
1955. **Prepare moderator guide**
196 
197 - Think-aloud instructions
198 - Non-leading prompts
199 - Post-task questions
200 
2016. **Reference:** See `references/usability-testing-frameworks.md` for full guide
202 
203---
204 
205### Workflow 4: Synthesize Research
206 
207**Situation:** You have raw research data (interviews, surveys, observations) and need actionable insights.
208 
209**Steps:**
210 
2111. **Code the data**
212 
213 Tag each data point:
214 - `[GOAL]` - What they want to achieve
215 - `[PAIN]` - What frustrates them
216 - `[BEHAVIOR]` - What they actually do
217 - `[CONTEXT]` - When/where they use product
218 - `[QUOTE]` - Direct user words
219 
2202. **Cluster similar patterns**
221 
222 ```
223 User A: Uses daily, advanced features, shortcuts
224 User B: Uses daily, complex workflows, automation
225 User C: Uses weekly, basic needs, occasional
226 
227 Cluster 1: A, B (Power Users)
228 Cluster 2: C (Casual User)
229 ```
230 
2313. **Calculate segment sizes**
232 
233 | Cluster | Users | % | Viability |
234 |---------|-------|---|-----------|
235 | Power Users | 18 | 36% | Primary persona |
236 | Business Users | 15 | 30% | Primary persona |
237 | Casual Users | 12 | 24% | Secondary persona |
238 
2394. **Extract key findings**
240 
241 For each theme:
242 - Finding statement
243 - Supporting evidence (quotes, data)
244 - Frequency (X/Y participants)
245 - Business impact
246 - Recommendation
247 
2485. **Prioritize opportunities**
249 
250 | Factor | Score 1-5 |
251 |--------|-----------|
252 | Frequency | How often does this occur? |
253 | Severity | How much does it hurt? |
254 | Breadth | How many users affected? |
255 | Solvability | Can we fix this? |
256 
2576. **Reference:** See `references/persona-methodology.md` for analysis framework
258 
259---
260 
261## Tool Reference
262 
263### persona_generator.py
264 
265Generates data-driven personas from user research data.
266 
267| Argument | Values | Default | Description |
268|----------|--------|---------|-------------|
269| format | (none), json | (none) | Output format |
270 
271**Sample Output:**
272 
273```
274============================================================
275PERSONA: Alex the Power User
276============================================================
277 
278📝 A daily user who primarily uses the product for work purposes
279 
280Archetype: Power User
281Quote: "I need tools that can keep up with my workflow"
282 
283👤 Demographics:
284 • Age Range: 25-34
285 • Location Type: Urban
286 • Tech Proficiency: Advanced
287 
288🎯 Goals & Needs:
289 • Complete tasks efficiently
290 • Automate workflows
291 • Access advanced features
292 
293😤 Frustrations:
294 • Slow loading times (14/20 users)
295 • No keyboard shortcuts
296 • Limited API access
297 
298💡 Design Implications:
299 → Optimize for speed and efficiency
300 → Provide keyboard shortcuts and power features
301 → Expose API and automation capabilities
302 
303📈 Data: Based on 45 users
304 Confidence: High
305```
306 
307**Archetypes Generated:**
308 
309| Archetype | Signals | Design Focus |
310|-----------|---------|--------------|
311| power_user | Daily use, 10+ features | Efficiency, customization |
312| casual_user | Weekly use, 3-5 features | Simplicity, guidance |
313| business_user | Work context, team use | Collaboration, reporting |
314| mobile_first | Mobile primary | Touch, offline, speed |
315 
316**Output Components:**
317 
318| Component | Description |
319|-----------|-------------|
320| demographics | Age range, location, occupation, tech level |
321| psychographics | Motivations, values, attitudes, lifestyle |
322| behaviors | Usage patterns, feature preferences |
323| needs_and_goals | Primary, secondary, functional, emotional |
324| frustrations | Pain points with evidence |
325| scenarios | Contextual usage stories |
326| design_implications | Actionable recommendations |
327| data_points | Sample size, confidence level |
328 
329---
330 
331## Quick Reference Tables
332 
333### Research Method Selection
334 
335| Question Type | Best Method | Sample Size |
336|---------------|-------------|-------------|
337| "What do users do?" | Analytics, observation | 100+ events |
338| "Why do they do it?" | Interviews | 8-15 users |
339| "How well can they do it?" | Usability test | 5-8 users |
340| "What do they prefer?" | Survey, A/B test | 50+ users |
341| "What do they feel?" | Diary study, interviews | 10-15 users |
342 
343### Persona Confidence Levels
344 
345| Sample Size | Confidence | Use Case |
346|-------------|------------|----------|
347| 5-10 users | Low | Exploratory |
348| 11-30 users | Medium | Directional |
349| 31+ users | High | Production |
350 
351### Usability Issue Severity
352 
353| Severity | Definition | Action |
354|----------|------------|--------|
355| 4 - Critical | Prevents task completion | Fix immediately |
356| 3 - Major | Significant difficulty | Fix before release |
357| 2 - Minor | Causes hesitation | Fix when possible |
358| 1 - Cosmetic | Noticed but not problematic | Low priority |
359 
360### Interview Question Types
361 
362| Type | Example | Use For |
363|------|---------|---------|
364| Context | "Walk me through your typical day" | Understanding environment |
365| Behavior | "Show me how you do X" | Observing actual actions |
366| Goals | "What are you trying to achieve?" | Uncovering motivations |
367| Pain | "What's the hardest part?" | Identifying frustrations |
368| Reflection | "What would you change?" | Generating ideas |
369 
370---
371 
372## Knowledge Base
373 
374Detailed reference guides in `references/`:
375 
376| File | Content |
377|------|---------|
378| `persona-methodology.md` | Validity criteria, data collection, analysis framework |
379| `journey-mapping-guide.md` | Mapping process, templates, opportunity identification |
380| `example-personas.md` | 3 complete persona examples with data |
381| `usability-testing-frameworks.md` | Test planning, task design, analysis |
382 
383---
384 
385## Validation Checklist
386 
387### Persona Quality
388- [ ] Based on 20+ users (minimum)
389- [ ] At least 2 data sources (quant + qual)
390- [ ] Specific, actionable goals
391- [ ] Frustrations include frequency counts
392- [ ] Design implications are specific
393- [ ] Confidence level stated
394 
395### Journey Map Quality
396- [ ] Scope clearly defined (persona, goal, timeframe)
397- [ ] Based on real user data, not assumptions
398- [ ] All layers filled (actions, touchpoints, emotions)
399- [ ] Pain points identified per stage
400- [ ] Opportunities prioritized
401 
402### Usability Test Quality
403- [ ] Research questions are testable
404- [ ] Tasks are realistic scenarios, not instructions
405- [ ] 5+ participants per design
406- [ ] Success metrics defined
407- [ ] Findings include severity ratings
408 
409### Research Synthesis Quality
410- [ ] Data coded consistently
411- [ ] Patterns based on 3+ data points
412- [ ] Findings include evidence
413- [ ] Recommendations are actionable
414- [ ] Priorities justified
415 
416## Related Skills
417 
418- **UI Design System** (`product-team/ui-design-system/`) — Research findings inform design system decisions
419- **Product Manager Toolkit** (`product-team/product-manager-toolkit/`) — Customer interview analysis complements persona research
420 

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