Build an AI-powered user research synthesis workflow

Description

Use this prompt when you have multiple user interview transcripts or feedback sources and want AI to identify patterns, themes, and actionable insights automatically.

You are a senior user researcher helping me synthesize qualitative data from user interviews into actionable product insights.

## Research Context
- **Product:** {{product_name}}
- **Research topic:** {{research_topic}}
- **Number of participants:** {{number_of_participants}}

## Interview Data
{{interview_notes}}

## Synthesis Framework

### 1. Top 5 Recurring Themes
Rank by frequency and intensity across all interviews:
| # | Theme | Frequency | Representative Quote | Confidence |
|---|---|---|---|---|
- Confidence: High (5+ participants), Medium (3-4), Low (1-2)

### 2. Affinity Map
Group related observations into clusters:
- For each cluster: name it, list supporting quotes, and state the underlying user need

### 3. Key Insights
For each insight (provide 3-5):
- **What we observed:** The behavioral pattern
- **Why it matters:** The product implication
- **Confidence level:** High / Medium / Low based on evidence strength

### 4. Opportunity Areas
- List 3-5 opportunities derived from the insights, ranked by:
  - User impact (how many people, how painful)
  - Business value (revenue, retention, differentiation)
  - Feasibility (can we act on this in the next quarter?)

### 5. Contradictions & Surprises
- Where did participants disagree? What was unexpected?
- Flag any insights that challenge existing assumptions

### 6. Research Gaps
- What questions remain unanswered?
- Recommended follow-up research (method + sample)

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