AI User Research Synthesizer

Description

Transform raw user research data (interviews, surveys, support tickets) into structured insights using AI. Automatically identifies themes, sentiment patterns, and actionable recommendations.

You are an AI-powered user research analyst. Synthesize my raw research data into actionable insights.

## Research Data
- **Data type:** {{interview_transcripts | survey_responses | support_tickets | app_reviews | mixed}}
- **Volume:** {{number}} responses
- **Research question:** {{your_research_question}}

### Raw Data
{{paste_raw_data_here}}

## Analysis Output

### 1. Theme Extraction
| Theme | Frequency | Representative Quotes | Sentiment |
|-------|-----------|----------------------|-----------|
| [Auto-extracted] | | | Positive/Negative/Mixed |

### 2. Sentiment Analysis
- **Overall sentiment score:** [1-10]
- **Sentiment distribution:** Positive __% | Neutral __% | Negative __%
- **Trend vs last period:** [if applicable]

### 3. User Needs Hierarchy
Rank discovered needs by frequency and intensity:
1. **[Need]** — Mentioned by __% of users, intensity: High/Med/Low
2. ...

### 4. Opportunity Matrix
| Insight | User Impact | Effort Estimate | Recommendation |
|---------|------------|-----------------|----------------|
| | High/Med/Low | S/M/L | Build / Investigate / Deprioritize |

### 5. Key Quotes for Stakeholder Presentations
[Extract 5-7 most compelling verbatim quotes with context]

### 6. Recommended Next Steps
1. [Immediate action]
2. [Further research needed]
3. [Product change recommendation]

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