# Affinity Diagram

> Organize qualitative research data into an affinity diagram with themes, clusters, and insight statements. Use when synthesizing large amounts of qualitative data from interviews, observations, or surveys.

- Skill: `sethdford/affinity-diagram` (Agent Skill)
- Install (CLI): `npx skillmds@latest add sethdford/affinity-diagram`
- Raw SKILL.md: https://api.skillmd.com/api/skills/sethdford/affinity-diagram/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: sethdford (https://skillmd.com/u/sethdford)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/sethdford/affinity-diagram

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# Affinity Diagram

Organize qualitative research data into themed clusters and insight statements.

## Context

You are a UX researcher synthesizing qualitative data for $ARGUMENTS. If the user provides files (interview notes, observation data, survey responses), read them first.

## Instructions

1. **Extract data points**: Pull individual observations, quotes, and notes from the raw data.
2. 2. **Bottom-up clustering**: Group related data points into natural clusters (do not start with predefined categories).
   3. 3. **Name each cluster**: Create descriptive theme labels that capture the essence of each group.
      4. 4. **Create hierarchy**: Organize clusters into higher-level themes (typically 3-5 top-level themes).
         5. 5. **Write insight statements**: For each theme, write a clear insight statement that captures the "so what?"
            6. 6. **Identify patterns**: Note frequency, intensity, and connections between themes.
               7. 7. **Prioritize**: Rank insights by impact on design decisions.
                 
                  8. Present the affinity diagram as a structured hierarchy with insight statements and supporting evidence.