Specialized skill for synthesizing qualitative user research into actionable insights. Analyzes interview transcripts, extracts patterns and themes, identifies pain points, creates affinity diagrams, and generates persona attributes from research data.
Specialized skill for synthesizing qualitative user research into actionable insights. Analyzes interview transcripts, extracts patterns and themes, identifies pain points, creates affinity diagrams, and generates persona attributes from research data.
Synthesize qualitative user research data into actionable product insights with thematic analysis and evidence-based recommendations.
Overview
This skill provides comprehensive capabilities for transforming raw user research data into structured insights. It supports interview transcript analysis, survey response synthesis, support ticket mining, and cross-source research aggregation.
Capabilities
Transcript Analysis
Analyze interview transcripts for patterns and themes
Extract key quotes and supporting evidence
Identify user pain points, needs, and goals
Tag and categorize research findings
Calculate insight confidence levels based on evidence
## Analysis Framework### Step 1: Initial Coding
For each transcript:
1. Read through completely for context
2. Highlight significant statements
3. Apply initial codes (open coding)
4. Note participant metadata
### Step 2: Pattern Recognition
Across transcripts:
1. Group similar codes
2. Identify recurring themes
3. Note frequency of mentions
4. Track contradicting evidence
### Step 3: Insight Generation
For each theme:
1. Define the insight clearly
2. List supporting evidence (3+ quotes)
3. Assess confidence level
4. Note actionable implications
Structured Coding Template
{"transcript_id":"INT-001","participant":{"id":"P001","segment":"power_user","tenure":"2_years"},"findings":[{"code":"onboarding_friction","theme":"First-time experience","quote":"I had no idea where to start...","timestamp":"00:12:34","sentiment":"negative","intensity":"high"}],"summary":{"key_pain_points":[],"unmet_needs":[],"positive_experiences":[],"feature_requests":[]}}
Affinity Diagram Generation
## Affinity Diagram Process### 1. Capture Observations- One observation per note
- Include source attribution
- Maintain original language
### 2. Group Bottom-Up- Cluster similar observations
- Name each cluster
- Create hierarchy of clusters
### 3. Output Format# Theme: [Theme Name]## Subtheme: [Subtheme Name]- Observation 1 (P001, INT-001)
- Observation 2 (P003, INT-003)
- Observation 3 (P007, INT-007)
### Evidence Strength- Strong: 5+ supporting observations
- Moderate: 3-4 supporting observations
- Emerging: 2 supporting observations
## JTBD Statement Format
When [situation/context],
I want to [motivation/goal],
So I can [expected outcome].
### Extraction Process1. Identify triggering situations in transcripts
2. Extract stated and unstated motivations
3. Map to desired outcomes
4. Categorize: Functional, Emotional, Social jobs
Pain Point Severity Matrix
Severity
Frequency
Impact
Priority
Critical
80%+ users
Blocks core task
P0
High
50-80% users
Significant friction
P1
Medium
25-50% users
Noticeable issue
P2
Low
<25% users
Minor annoyance
P3
Output Formats
Research Summary Report
# Research Synthesis Report## Executive Summary
[2-3 sentence overview]
## Research Methodology-**Method**: [Interviews/Surveys/etc.]
-**Participants**: [N participants]
-**Duration**: [Date range]
-**Research Questions**: [Key questions]
## Key Themes### Theme 1: [Name]
[Description and evidence]
### Theme 2: [Name]
[Description and evidence]
## Top Insights1.**Insight**: [Statement]
- Evidence: [Count]
- Confidence: [Level]
- Recommendation: [Action]
## Persona Implications
[How findings affect personas]
## Recommended Actions1. [Action item]
2. [Action item]
## Appendix- Full coding scheme
- Participant demographics
- Raw data references
Best Practices
Maintain Participant Anonymity: Use consistent IDs, not names
Preserve Original Language: Quote users verbatim when possible
Triangulate Sources: Seek confirmation across multiple sources
