{"id":"7bec1397-63e7-4197-b4c2-b4559b81bbee","shortId":"pMeNdW","kind":"skill","title":"user-research-synthesis","tagline":"Synthesize user interviews, survey results, feedback, and support tickets into structured insights. Identifies themes, pain points, and opportunities. Generates research reports ready for stakeholders.","description":"# User Research Synthesis Skill\n\nTurn raw user research data (interviews, surveys, feedback, support tickets) into structured, actionable insights.\n\n## When to Use\n- User has interview notes and needs to synthesize findings\n- User has survey results to analyze\n- User wants to identify patterns across user feedback\n- User says `/user-research-synthesis` followed by research data\n- Any time qualitative or quantitative user data needs structure\n\n## Framework: Research Synthesis (5 Steps)\n\n### Step 1: Organize Raw Data\n- **Source type**: Interviews / Surveys / Support tickets / App reviews / Usage data\n- **Sample size**: How many data points?\n- **User segments**: Who was included? Any notable gaps?\n- **Timeframe**: When was this data collected?\n\n### Step 2: Code & Theme\nIdentify recurring themes across the data:\n\n| Theme | Frequency | Sentiment | Example Quote |\n|-------|-----------|-----------|---------------|\n| [Theme 1] | X of Y participants | Positive/Negative/Mixed | \"...\" |\n| [Theme 2] | X of Y participants | | \"...\" |\n\nGroup themes into categories:\n- **Pain Points**: What's frustrating or broken\n- **Unmet Needs**: What users want but don't have\n- **Bright Spots**: What's working well (don't break these)\n- **Surprises**: Unexpected findings\n\n### Step 3: Prioritize Insights\nFor each insight, assess:\n- **Prevalence**: How many users mentioned this? (1 = rare, 5 = universal)\n- **Severity**: How painful is this? (1 = minor annoyance, 5 = deal-breaker)\n- **Actionability**: Can we do something about this? (1 = hard, 5 = clear path)\n\n**Priority Score = Prevalence x Severity x Actionability**\n\n### Step 4: Generate Recommendations\nFor the top 3-5 insights:\n- **Insight**: Clear statement of what we learned\n- **Evidence**: Supporting data points and quotes\n- **Implication**: What this means for the product\n- **Recommendation**: Specific next step (build, test, investigate further)\n- **Confidence**: High / Medium / Low (based on data quality)\n\n### Step 5: Research Report\n\n**Executive Summary** (2-3 sentences):\nWhat we studied, what we found, what we should do.\n\n**Key Findings** (3-5 bullet points):\nThe most important insights with supporting data.\n\n**Detailed Findings**:\nEach theme with quotes, data, and implications.\n\n**Recommendations**:\nPrioritized action items.\n\n**Methodology & Limitations**:\nHow research was done, sample biases, confidence level.\n\n## Input Formats Supported\n- **Raw interview notes**: Paste them in, the skill will code and theme them\n- **Survey results**: Paste summary stats or raw responses\n- **Support tickets**: Paste representative tickets for pattern analysis\n- **App store reviews**: Paste reviews for sentiment and theme analysis\n- **Mixed**: Combine multiple sources for triangulated insights\n\n## Output Format\nGenerate a clean research report in markdown. Use tables for theme coding. Include direct quotes as evidence. Be specific about confidence levels and limitations.\n\n## Tips for Better Synthesis\n- Look for contradictions — users who say opposite things often reveal a segmentation opportunity\n- Pay attention to workarounds — what users hack together reveals unmet needs\n- Note what users do vs. what they say — behavioral data trumps stated preferences\n- Flag sample bias — if you only talked to power users, say 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