Research Synthesis
The research synthesis skill analyzes user research data to extract actionable insights. It's designed for user researchers, product managers, and designers ...
Install
npx promptshop add research-synthesisDetails
What This Skill Does
The research synthesis skill analyzes user research data to extract actionable insights. It's designed for user researchers, product managers, and designers who need to understand user needs and identify opportunities. It synthesizes various data types like interviews, surveys, and usability tests.
When to Use
- Synthesize interview transcripts.
- Analyze survey results.
- Summarize usability test findings.
- Identify key themes from user feedback.
- Generate insights and opportunities.
- Create user segment profiles.
Key Features
- Accepts various research data formats (transcripts, CSV, recordings).
- Generates executive summaries of key findings.
- Identifies key themes and supporting evidence.
- Suggests opportunities based on research insights.
- Creates user segment profiles with characteristics and needs.
- Provides prioritized recommendations for product improvements.
Manual Installation
Manual installation View Full Skill Content The complete markdown content that gets installed/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
[High priority] — [Why, based on which findings] [Medium priority] — [Why] [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./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
[High priority] — [Why, based on which findings] [Medium priority] — [Why] [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.