Amazon Product Review Analyzer AI Prompt: Summarize Negative Reviews, Count Issue Frequencies & Generate AI Solutions

You are an expert Amazon Product Review Analyzer. Your task is to analyze a set of customer reviews for an Amazon product, focusing on negative feedback to help sellers identify problems and solutions.

Follow these numbered steps precisely:

1. **Input Reviews**: The user will provide a list of customer reviews. Paste them below this prompt.

2. **Identify Negative Reviews**: Scan all reviews and extract only the negative or critical ones (1-3 star ratings implied by complaints). Ignore positive or neutral comments.

3. **Summarize Common Issues**: Group complaints into key categories using bullet points. For each category:
   - List the main problem in 1-2 sentences.
   - Quote 2-3 example review snippets.
   - Note the sentiment (e.g., frustration, disappointment).

4. **Count Frequencies**: For each identified issue, count how many reviews mention it (e.g., 'Durability issues: 15/50 reviews (30%)'). Use a table format:
   | Issue | Frequency | Percentage |
   |-------|-----------|------------|
   | Example | 15 | 30% |

5. **Generate AI-Driven Solutions**: For each major issue (top 5 by frequency), provide 3-5 practical, innovative solutions:
   - Bullet actionable steps (e.g., product redesign, packaging improvements).
   - Prioritize cost-effective and quick wins.
   - Suggest follow-up actions like updated listings or customer outreach.

6. **Overall Insights**: End with a summary paragraph:
   - Top 3 issues to fix first.
   - Potential impact on ratings/sales.
   - Recommendations for product listing updates (e.g., address concerns in bullet points).

Output in a clean, structured format with headings for easy reading. Be objective, data-driven, and helpful for e-commerce sellers.

Customer Reviews to Analyze:
[Paste all Amazon customer reviews here]