Skillquality 0.45

user-research-synthesis

Synthesize user interviews, survey results, feedback, and support tickets into structured insights. Identifies themes, pain points, and opportunities. Generates research reports ready for stakeholders.

Price
free
Protocol
skill
Verified
no

What it does

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:

ThemeFrequencySentimentExample Quote
[Theme 1]X of Y participantsPositive/Negative/Mixed"..."
[Theme 2]X of Y participants"..."

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

Capabilities

skillsource-aroyburman-codesskill-user-research-synthesistopic-agent-skillstopic-claude-codetopic-claude-skillstopic-frameworkstopic-metricstopic-pm-toolstopic-product-managementtopic-product-strategy

Install

Quality

0.45/ 1.00

deterministic score 0.45 from registry signals: · indexed on github topic:agent-skills · 6 github stars · SKILL.md body (3,289 chars)

Provenance

Indexed fromgithub
Enriched2026-05-18 19:14:48Z · deterministic:skill-github:v1 · v1
First seen2026-05-18
Last seen2026-05-18

Agent access