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ux-researcher-designer

Kit de ferramentas de pesquisa e design de UX para Designers/Pesquisadores de UX Sênior, incluindo geração de personas baseada em dados, mapeamento de jornada, estruturas de teste de usabilidade e síntese de pesquisa. Utilize para pesquisa de usuário, criação de personas, mapeamento de jornada e validação de design.

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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"] } ] ``

  1. Run persona generator

```bash # Human-readable output python scripts/persona_generator.py

# JSON output for integration python scripts/persona_generator.py json ```

  1. 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? |

  1. Validate persona
  • Show to 3-5 real users: "Does this sound like you?"
  • Cross-check with support tickets
  • Verify against analytics data
  1. 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 |

  1. Gather journey data

Sources:

  • User interviews (ask "walk me through...")
  • Session recordings
  • Analytics (funnel, drop-offs)
  • Support tickets
  1. Map the stages

Typical B2B SaaS stages: `` Awareness → Evaluation → Onboarding → Adoption → Advocacy ``

  1. 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? ``

  1. Identify opportunities

Priority Score = Frequency × Severity × Solvability

  1. 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?" |

  1. 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 |

  1. 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

  1. Define success metrics

| Metric | Target | |--------|--------| | Completion rate | >80% | | Time on task | <2× expected | | Error rate | <15% | | Satisfaction | >4/5 |

  1. Prepare moderator guide
  • Think-aloud instructions
  • Non-leading prompts
  • Post-task questions
  1. 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
  1. 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) ```

  1. Calculate segment sizes

| Cluster | Users | % | Viability | |---------|-------|---|-----------| | Power Users | 18 | 36% | Primary persona | | Business Users | 15 | 30% | Primary persona | | Casual Users | 12 | 24% | Secondary persona |

  1. Extract key findings

For each theme:

  • Finding statement
  • Supporting evidence (quotes, data)
  • Frequency (X/Y participants)
  • Business impact
  • Recommendation
  1. 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? |

  1. 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:

|

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