UX Researcher & Designer

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

Trigger Terms
Workflows
Tool Reference
Quick Reference Tables
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:

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.

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

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