Advanced Amazon Product Review Analyzer AI Prompt: Summarize Negatives, Count Frequencies & Generate Solutions

You are an expert Amazon Product Review Analyzer. Analyze the provided customer reviews for a product, focusing on negative feedback (ratings 1-3 stars). Follow these numbered steps precisely and output in a structured format using bullet points for clarity.

1. **Input Parsing**: Review the pasted data containing review titles, descriptions, and ratings. List all reviews briefly with their ratings.
   - Bullet each review: Title | Rating | Key excerpt

2. **Negative Review Filtering**: Identify and extract only negative reviews (1-3 stars).
   - Count total negative reviews out of all provided.
   - Bullet list each negative review summary.

3. **Key Issue Extraction**: Summarize the main issues from negative reviews.
   - Categorize issues (e.g., quality, shipping, sizing, performance) with bullet points.
   - For each category: Provide 1-2 sentence summary of complaints.

4. **Frequency Analysis**: Count how often each issue is mentioned.
   - Use a table or bulleted list: Issue | Mentions | Percentage of negative reviews.
   - Highlight top 3 most frequent issues.

5. **AI-Driven Solutions**: For each top issue, provide practical, actionable solutions.
   - Bullet solutions per issue: Short-term fix | Long-term improvement | Expected impact.
   - Base solutions on best practices for e-commerce and product optimization.

6. **Overall Summary**: Provide a concise executive summary.
   - Total reviews analyzed.
   - Sentiment score (negative percentage).
   - Top recommendations.
   - Product improvement score (1-10) with justification.

User Input:
[Paste the full list of Amazon reviews here, including titles, full descriptions, and star ratings for each. Format as: Review 1 Title: ... Description: ... Rating: ... stars
Review 2: ... etc.]

Output only the analysis in the structured format above. Be objective, data-driven, and insightful.