| name | research-synthesis |
| description | Synthesize user research into themes, insights, and recommendations. Use when you have interview transcripts, survey results, usability test notes, support tickets, or NPS responses that need to be distilled into patterns, user segments, and prioritized next steps. |
| argument-hint | <research data, transcripts, or survey results> |
/research-synthesis
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Synthesize user research data into actionable insights. See the user-research skill for research methods, interview guides, and analysis frameworks.
Usage
/research-synthesis $ARGUMENTS
What I Accept
- Interview transcripts or notes
- Survey results (CSV, pasted data)
- Usability test recordings or notes
- Support tickets or feedback
- NPS/CSAT responses
- App store reviews
Output
## Research Synthesis: [Study Name]
**Method:** [Interviews / Survey / Usability Test] | **Participants:** [X]
**Date:** [Date range] | **Researcher:** [Name]
### Executive Summary
[3-4 sentence overview of key findings]
### Key Themes
#### Theme 1: [Name]
**Prevalence:** [X of Y participants]
**Summary:** [What this theme is about]
**Supporting Evidence:**
- "[Quote]" — P[X]
- "[Quote]" — P[X]
**Implication:** [What this means for the product]
#### Theme 2: [Name]
[Same format]
### Insights → Opportunities
| Insight | Opportunity | Impact | Effort |
|---------|-------------|--------|--------|
| [What we learned] | [What we could do] | High/Med/Low | High/Med/Low |
### User Segments Identified
| Segment | Characteristics | Needs | Size |
|---------|----------------|-------|------|
| [Name] | [Description] | [Key needs] | [Rough %] |
### Recommendations
1. **[High priority]** — [Why, based on which findings]
2. **[Medium priority]** — [Why]
3. **[Lower priority]** — [Why]
### Questions for Further Research
- [What we still don't know]
### Methodology Notes
[How the research was conducted, any limitations or biases to note]
If Connectors Available
If ~~user feedback is connected:
- Pull support tickets, feature requests, and NPS responses to supplement research data
- Cross-reference themes with real user complaints and requests
If ~~product analytics is connected:
- Validate qualitative findings with usage data and behavioral metrics
- Quantify the impact of identified pain points
If ~~knowledge base is connected:
- Search for prior research studies and findings to compare against
- Publish the synthesis to your research repository
Tips
- Include raw quotes — Direct participant quotes make insights credible and memorable.
- Separate observations from interpretations — "5 of 8 users clicked the wrong button" is an observation. "The button placement is confusing" is an interpretation.
- Quantify where possible — "Most users" is vague. "7 of 10 users" is specific.
