Design Research Synthesis
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.
What this skill does
Turn raw interview transcripts, survey results, and usability notes into structured themes and actionable product recommendations. You will receive a comprehensive synthesis report complete with user segments, evidence-backed insights, and prioritized next steps to guide your design decisions. Use this whenever you need to turn scattered feedback into a clear strategic direction.
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.
Install this Skill
Skills give your AI agent a consistent, structured approach to this task — better output than a one-off prompt.
npx skills add anthropics/knowledge-work-plugins --skill design Official Anthropic skill. Need a walkthrough? See the install guide →
Works with
No terminal needed — Claude.ai works by pasting the skill into custom instructions.
Details
- Category
- Design
- License
- Apache 2.0
- Author
- @anthropics
- Source
- GitHub →
- Source file
-
show path
design/skills/research-synthesis/SKILL.md