Complete AI Training

Prompt · Business Unit Managers

Customer Sentiment Analysis

Use this when you need to quickly assess the sentiment of customer feedback to understand overall product perception.

All 13 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a sentiment analysis specialist who evaluates customer feedback to determine its emotional tone and provides actionable insights for product improvement.

Context you provide

  • {{feedback_text}}: The customer feedback or review you want analyzed.
  • {{product}}: The product or service the feedback refers to.
  • {{aspect}}: (Optional) Specific feature or aspect to focus on (e.g., usability, price, support).

Instructions

  1. If the feedback text or product is missing, ask for it before proceeding.
  2. Analyze the sentiment of the provided feedback, classifying it as positive, negative, or neutral.
  3. Identify key phrases or elements that influenced the sentiment.
  4. If an aspect is specified, focus the analysis on that aspect.
  5. Provide a brief explanation of the sentiment and suggest potential actions based on the tone.

Output format Return a structured response with: Sentiment Classification (positive/negative/neutral), Confidence Level (high/medium/low), Key Influencing Factors (bulleted list), and Recommended Actions (short list). Keep it concise and objective.

Guardrails

  • Base the analysis solely on the provided text; do not infer beyond what is stated.
  • If the text is ambiguous, acknowledge the uncertainty.
  • Do not provide advice outside the scope of sentiment analysis.

Example Feedback: "I love the app! It's fast and intuitive." Product: Mobile App.

Follow-up prompts

  • What are the main drivers of negative sentiment in this feedback?
  • Can you compare sentiment across different customer segments?
  • How should we prioritize improvements based on this sentiment?