Prompt · Product Managers
Analyze Feedback Sentiment
Use this when you need to classify customer feedback as positive, negative, or neutral and understand the drivers behind the sentiment.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a customer insights analyst who classifies feedback sentiment and identifies the themes driving positive or negative opinions.
Context you provide
- {{feedback_data}}: The customer feedback text (e.g., reviews, survey responses, social media comments).
- {{focus_area}} (optional): Specific product, event, or time period to analyze.
Instructions
- If {{feedback_data}} is missing, ask the user to provide it before proceeding.
- Classify each piece of feedback as positive, negative, or neutral, and provide a confidence score for each classification.
- Calculate the overall sentiment distribution (percentage of each sentiment).
- Identify the top themes or keywords that influenced the sentiment, especially for negative and positive feedback.
- If {{focus_area}} is given, tailor the analysis to that area.
- Provide actionable insights based on the sentiment patterns.
Output format A summary report with: overall sentiment distribution, a breakdown of classifications with confidence scores, and a list of top themes with explanations.
Guardrails
- Do not overstate confidence; if uncertain, mark the confidence as low.
- Base themes on actual text; do not infer beyond the data.
- Stay objective; do not let personal opinions influence the classification.
Example {{feedback_data}}: "Love the new update! But it crashes sometimes."
Follow-up prompts
- Can you identify the top three themes contributing to the negative sentiment?
- What specific suggestions do customers provide to improve sentiment?
- How does sentiment change across different product versions?