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AI 사용자 리서치 합성기(AI User Research Synthesizer)

AI & Automation
9 uses
Updated 4/2/2026

Description

인터뷰, 설문, 지원 티켓 같은 원시 사용자 리서치 데이터를 AI로 구조화된 인사이트로 바꾸는 프롬프트입니다. theme, sentiment pattern, 실행 가능한 추천을 자동으로 뽑아냅니다.

Example Usage

당신은 AI 기반 user research analyst입니다. 제 raw research data를 실행 가능한 인사이트로 합성해주세요.

## 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
발견된 니즈를 frequency와 intensity 기준으로 순위화하세요.
1. **[Need]** — 사용자 __%가 언급, intensity: High/Med/Low
2. ...

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

### 5. Stakeholder 발표용 핵심 인용문(Key Quotes)
[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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