Research Synthesis
Transform raw user research (interviews, surveys, usability tests, support tickets) into structured insights that drive design and product decisions.
Synthesis Process
Phase 1 — Ingest Raw Data
- If
$ARGUMENTS is a file path, read it.
- Identify the research type:
- Interviews: transcripts, notes
- Surveys: quantitative + open-ended responses
- Usability tests: task success/failure, observations, quotes
- Support tickets: categorized complaints, feature requests
- Analytics: behavioral data, funnel metrics
- If data is insufficient, ask what research was conducted and key findings.
Phase 2 — Code & Cluster
Affinity Mapping
- Extract observations: Pull discrete data points — quotes, behaviors, pain points, needs.
- Tag each observation with:
- Participant/source ID
- Sentiment: positive / negative / neutral
- Category: behavior / pain-point / need / workaround / delight / confusion
- Cluster into themes: Group related observations. A theme needs 3+ observations from 2+ sources.
- Name each theme: Use user-centric language ("Users distrust auto-save" not "Save feature issue").
Phase 3 — Generate Insights
For each theme, produce a structured insight:
### Insight: {descriptive title}
**Observation**: {What we saw — grounded in data}
- "{direct quote}" — P3
- "{direct quote}" — P7
- {N} of {total} participants exhibited this behavior
**Interpretation**: {What it means — our analysis}
**Implication**: {What we should do about it — actionable recommendation}
**Confidence**: High / Medium / Low
- Based on: {N} sources, {method type}, consistency of signal
**Priority**: {Critical / High / Medium / Low}
- Impact: {how many users affected, severity of pain}
- Effort: {estimated implementation complexity}
Phase 4 — Prioritization Matrix
Plot insights on an impact/effort matrix:
## Priority Matrix
### High Impact, Low Effort (Do First)
1. {Insight title} — {one-line summary}
### High Impact, High Effort (Plan)
1. {Insight title} — {one-line summary}
### Low Impact, Low Effort (Quick Wins)
1. {Insight title} — {one-line summary}
### Low Impact, High Effort (Deprioritize)
1. {Insight title} — {one-line summary}
Phase 5 — Output Report
## Research Synthesis — {project/study name}
### Study Overview
- **Method**: {interviews / survey / usability test / mixed}
- **Participants**: {N} participants, {demographics or segments}
- **Date**: {when research was conducted}
- **Research questions**: {what we were trying to learn}
### Key Themes
1. {Theme name} — {N} observations from {N} sources
2. {Theme name} — ...
### Insights (ordered by priority)
{structured insights from Phase 3}
### Recommendations
1. **{Action}** — addresses insights {1, 3}. Priority: {High}
2. **{Action}** — addresses insight {2}. Priority: {Medium}
### Open Questions
- {Questions the research raised but didn't answer}
- {Suggested follow-up research}
### Raw Data Summary
- Total observations coded: {N}
- Themes identified: {N}
- Insights generated: {N}
Quality Standards
- Ground every insight in data: No interpretation without at least 2 supporting observations.
- Distinguish observation from interpretation: Keep them separate — observations are facts, interpretations are analysis.
- Include dissenting data: If 8/10 users loved a feature but 2 hated it, note both.
- Quantify where possible: "Most users" is weak. "7 of 10 users" is strong.
- Preserve participant voices: Include direct quotes — they're the most compelling evidence.
- Flag confidence levels: Be honest about what the data supports vs. what's inferred.
Quality Checklist
Edge Cases
- If input data is incomplete, state assumptions explicitly and flag gaps
- For time-sensitive situations, prioritize speed over comprehensiveness
- If multiple stakeholders have conflicting needs, document the tradeoffs
- For first-time use, start with a simplified version and iterate
- Adapt the depth and detail to the audience's expertise level
1---2name: research-synthesis3description: Synthesize user research into actionable themes, insights, and recommendations. TRIGGER when: user says "synthesize research", "analyze interviews", "find patterns", "research themes", "insight mapping", or has raw research data to distill.4---56# Research Synthesis78Transform raw user research (interviews, surveys, usability tests, support tickets) into structured insights that drive design and product decisions.910## Synthesis Process1112### Phase 1 — Ingest Raw Data13141. If `$ARGUMENTS` is a file path, read it.152. Identify the research type:16 - **Interviews**: transcripts, notes17 - **Surveys**: quantitative + open-ended responses18 - **Usability tests**: task success/failure, observations, quotes19 - **Support tickets**: categorized complaints, feature requests20 - **Analytics**: behavioral data, funnel metrics213. If data is insufficient, ask what research was conducted and key findings.2223### Phase 2 — Code & Cluster2425#### Affinity Mapping26271. **Extract observations**: Pull discrete data points — quotes, behaviors, pain points, needs.282. **Tag each observation** with:29 - Participant/source ID30 - Sentiment: positive / negative / neutral31 - Category: behavior / pain-point / need / workaround / delight / confusion323. **Cluster into themes**: Group related observations. A theme needs 3+ observations from 2+ sources.334. **Name each theme**: Use user-centric language ("Users distrust auto-save" not "Save feature issue").3435### Phase 3 — Generate Insights3637For each theme, produce a structured insight:3839```40### Insight: {descriptive title}4142**Observation**: {What we saw — grounded in data}43- "{direct quote}" — P344- "{direct quote}" — P745- {N} of {total} participants exhibited this behavior4647**Interpretation**: {What it means — our analysis}4849**Implication**: {What we should do about it — actionable recommendation}5051**Confidence**: High / Medium / Low52- Based on: {N} sources, {method type}, consistency of signal5354**Priority**: {Critical / High / Medium / Low}55- Impact: {how many users affected, severity of pain}56- Effort: {estimated implementation complexity}57```5859### Phase 4 — Prioritization Matrix6061Plot insights on an impact/effort matrix:6263```64## Priority Matrix6566### High Impact, Low Effort (Do First)671. {Insight title} — {one-line summary}6869### High Impact, High Effort (Plan)701. {Insight title} — {one-line summary}7172### Low Impact, Low Effort (Quick Wins)731. {Insight title} — {one-line summary}7475### Low Impact, High Effort (Deprioritize)761. {Insight title} — {one-line summary}77```7879### Phase 5 — Output Report8081```82## Research Synthesis — {project/study name}8384### Study Overview85- **Method**: {interviews / survey / usability test / mixed}86- **Participants**: {N} participants, {demographics or segments}87- **Date**: {when research was conducted}88- **Research questions**: {what we were trying to learn}8990### Key Themes911. {Theme name} — {N} observations from {N} sources922. {Theme name} — ...9394### Insights (ordered by priority)95{structured insights from Phase 3}9697### Recommendations981. **{Action}** — addresses insights {1, 3}. Priority: {High}992. **{Action}** — addresses insight {2}. Priority: {Medium}100101### Open Questions102- {Questions the research raised but didn't answer}103- {Suggested follow-up research}104105### Raw Data Summary106- Total observations coded: {N}107- Themes identified: {N}108- Insights generated: {N}109```110111## Quality Standards112113- **Ground every insight in data**: No interpretation without at least 2 supporting observations.114- **Distinguish observation from interpretation**: Keep them separate — observations are facts, interpretations are analysis.115- **Include dissenting data**: If 8/10 users loved a feature but 2 hated it, note both.116- **Quantify where possible**: "Most users" is weak. "7 of 10 users" is strong.117- **Preserve participant voices**: Include direct quotes — they're the most compelling evidence.118- **Flag confidence levels**: Be honest about what the data supports vs. what's inferred.119120## Quality Checklist121122- [ ] Output is specific and actionable, not generic123- [ ] All relevant inputs have been gathered before producing output124- [ ] Recommendations are prioritized by impact125- [ ] Stakeholders and audience are identified126- [ ] Output format matches the audience's needs127- [ ] Key assumptions are documented128- [ ] Follow-up actions have clear owners129130## Edge Cases131132- If input data is incomplete, state assumptions explicitly and flag gaps133- For time-sensitive situations, prioritize speed over comprehensiveness134- If multiple stakeholders have conflicting needs, document the tradeoffs135- For first-time use, start with a simplified version and iterate136- Adapt the depth and detail to the audience's expertise level