User Research Synthesis Skill
This skill helps analyze user research data and transform it into actionable insights following a structured methodology.
Required Inputs
Ask the user for these if not provided:
- Research data (transcripts, notes, survey results, or summary bullets)
- Research method (interviews, surveys, usability tests, etc.)
- Number of participants and their profiles (role, context)
- Research questions the study aimed to answer
Synthesis Framework
1. Data Collection Overview
- Research Type: Interviews, surveys, usability tests, etc.
- Participant Profile: Demographics, segments, sample size
- Research Questions: What we sought to learn
- Methodology: How data was collected
2. Key Themes Identification
Organize findings into themes using this structure:
Theme Name
- Description: What this theme represents
- Prevalence: How many participants mentioned this (e.g., "8 out of 12 participants")
- Supporting Quotes: 2-3 representative quotes
- Implication: What this means for our product
Aim for 4-8 major themes per research effort.
3. Pain Points Analysis
For each identified pain point:
- Pain Point: Clear description
- Severity: High/Medium/Low (based on impact and frequency)
- Current Workaround: How users deal with it today
- Evidence: Specific examples from research
4. Feature Requests
Categorize requests:
- Must-Have: Critical needs blocking user success
- High Value: Would significantly improve experience
- Nice-to-Have: Incremental improvements
For each request:
- Request: What users asked for
- Frequency: How often it came up
- User Quote: Representative example
- Underlying Need: Why they want this (dig deeper than surface request)
5. User Workflow Insights
Document actual workflows observed:
- Current State: How users accomplish tasks today
- Pain Points: Where they struggle
- Ideal State: What they wish they could do
- Opportunities: Where we can add value
6. Segmentation Insights
If research reveals distinct user segments:
- Segment Name: Descriptive label
- Characteristics: What defines this segment
- Unique Needs: How their needs differ
- Size/Importance: Relative weight for prioritization
7. Competitive Insights
If users mentioned competitors or alternatives:
- Competitor/Alternative: What they use
- Why They Use It: What it does well
- Gaps: What it doesn't do
- Switching Barriers: Why they don't switch fully
8. Recommendations
Prioritized recommendations based on insights:
High Priority
- Recommendation with supporting evidence
- Expected impact
Medium Priority
- Recommendation with supporting evidence
- Expected impact
Low Priority / Future Consideration
- Recommendation with supporting evidence
- Expected impact
9. Open Questions
Research gaps identified:
- What we still need to understand
- Suggested follow-up research
- Uncertainties requiring validation
Analysis Guidelines
When synthesizing interviews:
- Look for patterns across multiple participants
- Note both what users say AND what they do
- Pay attention to emotional reactions
- Identify jobs-to-be-done, not just feature requests
When analyzing quotes:
- Use verbatim quotes in "quotation marks"
- Attribute quotes: [Participant ID, Role, Context]
- Select quotes that illustrate patterns, not outliers
- Include both positive and negative feedback
When identifying themes:
- Use descriptive names, not generic labels
- Provide evidence for each theme
- Quantify when possible ("7 out of 10 users...")
- Connect themes to business objectives
Quality Checks
- Themes identify patterns across multiple participants, not individual responses
- Insights connect to specific product decisions, not just observations
- Each claim includes supporting evidence (quotes, counts, or examples)
- Observations and interpretations are clearly separated
- Findings are prioritised by impact, not just listed
Anti-Patterns
- Do not list every individual comment — synthesis must identify patterns across participants
- Do not make interpretive leaps without supporting evidence from the data
- Do not focus on feature requests before understanding the underlying problem — always identify the job-to-be-done first
- Do not ignore contradictory data — conflicting findings must be surfaced and noted
- Do not present results without quantifying prevalence — state how many participants held each view
Example Theme
**Theme: Information Overload During Onboarding**
**Description**: Users consistently expressed feeling overwhelmed by the amount of information presented during initial setup, leading to incomplete onboarding and delayed time-to-value.
**Prevalence**: 9 out of 12 participants mentioned this issue unprompted
**Supporting Quotes**:
- "I just wanted to get started, but it felt like I needed to read a manual first" [P3, Marketing Manager]
- "By the third screen of instructions, I started clicking 'Next' without reading" [P7, Sales Rep]
- "I wish there was a 'quick start' option for people like me who just want to try it" [P11, Product Designer]
**Implication**: Our current onboarding flow prioritizes completeness over engagement. We should consider a progressive disclosure approach where users can start using the product quickly and learn advanced features contextually.
**Recommended Action**:
- Design a "Quick Start" path that gets users to first value in <3 minutes
- Move advanced configuration to contextual help within the app
- Test with 5-10 new users before full rollout
- Expected impact: +20-30% activation rate improvement
Template Output Structure
When synthesizing research, use this structure:
# User Research Synthesis: [Research Topic]
## Research Overview
- **Date**: [Date range]
- **Methodology**: [Interview/Survey/Testing]
- **Participants**: [Number] [User types]
- **Research Questions**:
1. [Question 1]
2. [Question 2]
3. [Question 3]
## Executive Summary
[2-3 sentence overview of key findings and implications]
## Key Themes
### Theme 1: [Theme Name]
[Full theme documentation as shown in example above]
### Theme 2: [Theme Name]
[Full theme documentation]
[Continue with 4-8 themes]
## Pain Points Summary
| Pain Point | Severity | Frequency | Current Workaround |
|------------|----------|-----------|-------------------|
| [Pain 1] | High | 10/12 users | [How they cope] |
| [Pain 2] | Medium | 7/12 users | [How they cope] |
## Feature Requests
### Must-Have
1. **[Request]** - Mentioned by [X] participants
- Quote: "[Representative quote]"
- Underlying need: [Why they want this]
### High Value
[Similar structure]
### Nice-to-Have
[Similar structure]
## Recommendations
### High Priority (0-3 months)
1. **[Recommendation]**
- Supporting evidence: [Data from research]
- Expected impact: [What will improve]
- Effort estimate: [Rough sizing]
### Medium Priority (3-6 months)
[Similar structure]
### Future Consideration (6+ months)
[Similar structure]
## Open Questions
1. [Question requiring more research]
2. [Uncertainty to validate]
3. [Follow-up study needed]
## Appendix
- Interview guide used
- Full participant demographics
- Raw notes/transcripts (link)