danielpradilla Research Evidence Brief
Use this workflow to 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 Standards
Good Synthesis:
- Identifies patterns, not just individual responses
- Connects insights to product decisions
- Includes supporting evidence for each claim
- Separates observations from interpretations
- Prioritizes findings by impact
Poor Synthesis:
- Lists every individual comment
- Lacks evidence or examples
- Makes unsupported leaps
- Focuses on solutions before understanding problems
- Ignores contradictory data