UX Researcher & Designer

Comprehensive toolkit for user-centered research and experience design with data-driven approaches.

Overview

This skill provides professional UX research and design capabilities including persona generation from real user data, customer journey mapping, usability testing frameworks, and research synthesis methods.

When to Use This Skill

• Creating data-driven user personas
• Analyzing user behavior patterns and insights
• Mapping customer journeys and touchpoints
• Conducting usability research and validation
• Synthesizing research data into actionable insights
• Generating design implications from user data

Core Capabilities

1. Data-Driven Persona Generation

Create research-backed personas from quantitative and qualitative user data:

• Analyze user behavior patterns from analytics
• Identify persona archetypes automatically
• Extract psychographics (motivations, values, attitudes)
• Generate realistic usage scenarios
• Provide confidence scoring based on sample size
• Derive design implications from persona data

2. Persona Archetypes

Built-in archetype templates for common user types:

• Power User: Tech-savvy, frequent user, efficiency-focused
• Casual User: Occasional user, values simplicity and ease-of-use
• Business User: ROI-focused, team collaboration oriented
• Mobile First: Primarily mobile usage, on-the-go access

3. Customer Journey Mapping

Map complete user journeys with:

• Touchpoint identification
• Pain point analysis
• Opportunity discovery
• Emotion mapping across journey stages

4. Usability Testing Frameworks

Structured approaches for:

• Test plan creation
• Success metrics definition
• User task scenarios
• Observation frameworks

5. Research Synthesis

Transform raw research into insights:

• Pattern identification across users
• Theme extraction from interviews
• Quantitative and qualitative data integration
• Actionable design recommendations

Available Tools

Python Script: persona_generator.py

Location: scripts/persona_generator.py

Purpose: Generate comprehensive, data-driven user personas from user data and optional interview insights.

Usage:

# JSON output
python scripts/persona_generator.py json

# Human-readable output
python scripts/persona_generator.py

Features:

• Analyzes usage frequency, feature usage, device patterns
• Identifies persona archetype based on behavior patterns
• Aggregates demographics (age, location, tech proficiency)
• Extracts psychographics (motivations, values, lifestyle)
• Generates usage scenarios with context and pain points
• Calculates confidence level based on sample size
• Provides design implications for each persona

Input Data Structure:

user_data = [
    {
        'user_id': 'user_1',
        'age': 28,
        'usage_frequency': 'daily',  # daily, weekly, monthly
        'features_used': ['dashboard', 'reports', 'settings'],
        'primary_device': 'desktop',  # desktop, mobile, tablet
        'usage_context': 'work',  # work, personal
        'tech_proficiency': 7,  # 1-10 scale
        'pain_points': ['slow loading', 'confusing UI']
    }
    # ... more users
]

Output Includes:

• Persona name and archetype
• Demographics and psychographics
• Goals, needs, and frustrations
• Behavior patterns and feature preferences
• Usage scenarios with pain points
• Design implications
• Data confidence metrics

TypeScript Script: persona-generator.ts

Location: scripts/persona-generator.ts

Purpose: Same functionality as Python version, integrated with Node.js/TypeScript ecosystem.

Usage:

# JSON output
ts-node scripts/persona-generator.ts --format=json

# Pretty output
ts-node scripts/persona-generator.ts

TypeScript Advantages:

• Type-safe data structures
• Better IDE integration
• Easy integration with existing Node.js projects
• Modern async/await patterns

Design Implications Framework

Each generated persona includes specific design implications based on their characteristics:

For High-Frequency Users:

• Optimize for speed and efficiency
• Provide keyboard shortcuts and power features
• Minimize friction in common workflows

For Casual Users:

• Focus on discoverability and clear guidance
• Simplify onboarding experience
• Reduce cognitive load

For Mobile Users:

• Mobile-first responsive design
• Touch-optimized interactions
• Offline capability considerations

For Business Users:

• Professional visual design
• Enterprise features (SSO, audit logs, team management)
• Integration with business tools

Best Practices

Data Collection

1. Minimum Sample Size: 20+ users for Medium confidence, 50+ for High confidence
2. Mix Methods: Combine quantitative analytics with qualitative interviews
3. Regular Updates: Refresh personas quarterly or after major product changes
4. Validation: Test personas against real user behavior continuously

Persona Usage

1. Share Widely: Make personas accessible to entire product team
2. Reference Often: Use in feature discussions and design reviews
3. Update Regularly: Keep personas current as user base evolves
4. Measure Impact: Track how persona-driven decisions affect metrics

Research Synthesis

1. Document Everything: Keep detailed notes from all research activities
2. Look for Patterns: Identify recurring themes across multiple users
3. Prioritize Insights: Focus on actionable findings with high impact
4. Validate Assumptions: Test hypotheses with additional research

Context Levels

Level 1 - Minimal (Always Loaded)

• Core UX research principles
• Persona archetype definitions
• Basic usage patterns

Level 2 - Detailed (Load on Request)

• Complete persona generation methodology
• Journey mapping frameworks
• Usability testing templates
• Research synthesis techniques

Level 3 - Full (Scripts and Examples)

• Working Python and TypeScript scripts
• Sample data structures
• Complete persona examples
• Integration code samples

Integration with Other Skills

Works well with:

• ui-design-system: Use personas to inform design token decisions
• frontend-specialist: Apply persona insights to component design
• testing-fundamentals: Create test scenarios based on persona behaviors
• accessibility-specialist: Ensure designs work for all persona types

References

UX Research Methods:

• Nielsen Norman Group UX Research Guidelines
• IDEO Human-Centered Design Toolkit
• Google Design Sprint Methodology

Persona Creation:

• Alan Cooper's "The Inmates Are Running the Asylum"
• Data-Driven Personas (Jansen et al.)
• Jobs To Be Done Framework

Journey Mapping:

• Adaptive Path's Guide to Experience Mapping
• Service Design Toolkit

Version History

v1.0.0 - Initial release

• Data-driven persona generation
• Python and TypeScript implementations
• 4 persona archetype templates
• Design implications framework
• Confidence scoring system

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Maintained by: Primadata Enhanced Toolkit Source: Based on claude-skills repository by Alireza Rezvani Last Updated: November 2025