user-research

What this skill does

# User Research

## Research Methodologies

### User Interviews
- **One-on-One Interviews**: Deep, qualitative conversations with individual users
- **Semi-Structured**: Use a guide but allow flexibility to explore unexpected topics
- **Open-Ended Questions**: Ask questions that encourage detailed responses
- **Active Listening**: Listen more than you speak, probe for deeper understanding
- **Recording**: Record interviews (with permission) for later analysis
- **Interview Length**: 30-60 minutes is optimal for maintaining engagement

### Surveys
- **Survey Design**: Keep surveys short and focused (5-10 minutes max)
- **Question Types**: Use a mix of multiple choice, rating scales, and open-ended questions
- **Avoid Bias**: Use neutral language and avoid leading questions
- **Pilot Testing**: Test surveys with a small group before full distribution
- **Distribution Channels**: Email, in-app, social media, or dedicated survey platforms
- **Response Rates**: Expect 10-20% response rate for email surveys

### Usability Testing
- **Moderated Testing**: Researcher guides participants through tasks
- **Unmoderated Testing**: Participants complete tasks independently
- **Think-Aloud Protocol**: Ask participants to verbalize their thoughts
- **Task Design**: Create realistic tasks that represent actual user goals
- **Metrics**: Track task completion rate, time on task, error rate, and satisfaction
- **Sample Size**: 5 users reveal 80% of usability issues

### Card Sorting
- **Open Card Sort**: Users create their own categories
- **Closed Card Sort**: Users sort into predefined categories
- **Hybrid Approach**: Combine both methods for comprehensive insights
- **Tools**: Use online tools for remote card sorting sessions
- **Analysis**: Look for patterns and consensus in how users organize information
- **Application**: Inform information architecture and navigation design

## Persona Creation

### Persona Development
- **Research-Based**: Personas should be based on real research data
- **Demographics**: Age, gender, location, education, occupation
- **Psychographics**: Goals, motivations, frustrations, attitudes
- **Behaviors**: How they interact with products, technology preferences
- **Quotes**: Include real quotes from interviews to bring personas to life
- **Scenarios**: Describe typical use cases and contexts

### User Journey Mapping
- **Touchpoints**: List all interactions across channels and devices
- **Emotions**: Map user emotions at each touchpoint
- **Pain Points**: Identify areas of frustration or difficulty
- **Opportunities**: Find moments to delight users or improve experience
- **Timeline**: Show the sequence of interactions over time
- **Channels**: Include all channels (web, mobile, email, in-person)

## User Stories and Use Cases

### User Story Format
- **Template**: "As a [type of user], I want [goal] so that [benefit]"
- **Acceptance Criteria**: Define specific conditions for story completion
- **Priority**: Rank stories by business value and user need
- **Estimation**: Provide effort estimates for planning
- **Dependencies**: Identify relationships between stories

### Use Case Development
- **Actors**: Identify primary and secondary actors
- **Preconditions**: Define conditions before use case begins
- **Main Flow**: Describe the primary success scenario
- **Alternative Flows**: Document alternative paths and edge cases
- **Postconditions**: Define the state after use case completion
- **Exceptions**: Handle error conditions and failures

## Research Analysis and Insight Extraction

### Data Synthesis
- **Affinity Diagramming**: Group related findings into themes
- **Pattern Recognition**: Identify recurring themes and insights
- **Triangulation**: Validate findings across multiple research methods
- **Quantitative Analysis**: Use statistical methods for survey data
- **Qualitative Analysis**: Use thematic analysis for interview data

### Insight Extraction
- **So What?**: Ask why findings matter and what they imply
- **Now What?**: Determine actionable next steps
- **Prioritization**: Rank insights by impact and feasibility
- **Validation**: Plan how to validate insights with additional research
- **Communication**: Present insights in a clear, compelling way

## A/B Testing and Experiment Design

### Experiment Design
- **Hypothesis**: Clearly state what you're testing and why
- **Variables**: Define independent (what you change) and dependent (what you measure) variables
- **Control Group**: Include a group that doesn't see the change
- **Sample Size**: Calculate required sample size for statistical significance
- **Duration**: Run tests long enough to reach statistical significance
- **Metrics**: Choose appropriate metrics (conversion, engagement, satisfaction)

### A/B Testing Best Practices
- **Test One Variable**: Change only one element at a time
- **Statistical Significance**: Use proper statistical methods to analyze results
- **Segmentation**: Analyze results by user segments
- **Iterative Testing**: Build on learnings from previous tests
- **Ethical Considerations**: Consider impact on user experience and privacy