User Research Synthesis

User Research Synthesis Skill

Turn raw user research data (interviews, surveys, feedback, support tickets) into structured, actionable insights.

When to Use

• User has interview notes and needs to synthesize findings
• User has survey results to analyze
• User wants to identify patterns across user feedback
• User says /user-research-synthesis followed by research data
• Any time qualitative or quantitative user data needs structure

Framework: Research Synthesis (5 Steps)

Step 1: Organize Raw Data

• Source type: Interviews / Surveys / Support tickets / App reviews / Usage data
• Sample size: How many data points?
• User segments: Who was included? Any notable gaps?
• Timeframe: When was this data collected?

Step 2: Code & Theme

Identify recurring themes across the data:

Group themes into categories:

• Pain Points: What's frustrating or broken
• Unmet Needs: What users want but don't have
• Bright Spots: What's working well (don't break these)
• Surprises: Unexpected findings

Step 3: Prioritize Insights

For each insight, assess:

• Prevalence: How many users mentioned this? (1 = rare, 5 = universal)
• Severity: How painful is this? (1 = minor annoyance, 5 = deal-breaker)
• Actionability: Can we do something about this? (1 = hard, 5 = clear path)

Priority Score = Prevalence x Severity x Actionability

Step 4: Generate Recommendations

For the top 3-5 insights:

• Insight: Clear statement of what we learned
• Evidence: Supporting data points and quotes
• Implication: What this means for the product
• Recommendation: Specific next step (build, test, investigate further)
• Confidence: High / Medium / Low (based on data quality)

Step 5: Research Report

Executive Summary (2-3 sentences): What we studied, what we found, what we should do.

Key Findings (3-5 bullet points): The most important insights with supporting data.

Detailed Findings: Each theme with quotes, data, and implications.

Recommendations: Prioritized action items.

Methodology & Limitations: How research was done, sample biases, confidence level.

Input Formats Supported

• Raw interview notes: Paste them in, the skill will code and theme them
• Survey results: Paste summary stats or raw responses
• Support tickets: Paste representative tickets for pattern analysis
• App store reviews: Paste reviews for sentiment and theme analysis
• Mixed: Combine multiple sources for triangulated insights

Output Format

Generate a clean research report in markdown. Use tables for theme coding. Include direct quotes as evidence. Be specific about confidence levels and limitations.

Tips for Better Synthesis

• Look for contradictions — users who say opposite things often reveal a segmentation opportunity
• Pay attention to workarounds — what users hack together reveals unmet needs
• Note what users do vs. what they say — behavioral data trumps stated preferences
• Flag sample bias — if you only talked to power users, say so