user-research-analysis

SKILL.md

User Research Analysis

Table of Contents

Overview

When to Use

Quick Start

Reference Guides

Best Practices

Overview

Effective research analysis transforms raw data into actionable insights that guide product development and design.

When to Use

Synthesis of user interviews and surveys

Identifying patterns and themes

Validating design assumptions

Prioritizing user needs

Communicating insights to stakeholders

Informing design decisions

Quick Start

Minimal working example:

# Analyze qualitative and quantitative data

class ResearchAnalysis:
    def synthesize_interviews(self, interviews):
        """Extract themes and insights from interviews"""
        return {
            'interviews_analyzed': len(interviews),
            'methodology': 'Thematic coding and affinity mapping',
            'themes': self.identify_themes(interviews),
            'quotes': self.extract_key_quotes(interviews),
            'pain_points': self.identify_pain_points(interviews),
            'opportunities': self.identify_opportunities(interviews)
        }

    def identify_themes(self, interviews):
        """Find recurring patterns across interviews"""
        themes = {}
        theme_frequency = {}

        for interview in interviews:
            for statement in interview['statements']:
                theme = self.categorize_statement(statement)
                theme_frequency[theme] = theme_frequency.get(theme, 0) + 1

        # Sort by frequency
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide
Contents

Research Synthesis Methods
Research Synthesis Methods

Affinity Mapping
Affinity Mapping

Insight Documentation
Insight Documentation

Research Validation Matrix
Research Validation Matrix

Best Practices

✅ DO

Use multiple research methods

Triangulate findings across sources

Document quotes and evidence

Look for patterns and frequency

Separate findings from interpretation

Validate findings with users

Share insights across team

Connect to design decisions

Document methodology

Iterate research approach based on learnings

❌ DON'T

Over-interpret small samples

Ignore conflicting data

Base decisions on single data point

Skip documentation

Cherry-pick quotes that support assumptions

Present without supporting evidence

Forget to note limitations

Analyze without involving participants

Create insights without actionable recommendations

Let research sit unused

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