Skills 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.

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 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