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Prompt · Insurance Claims Managers

Customer Sentiment Analysis

Use this when you need to analyze customer feedback to identify pain points and improve claims experience.

All 22 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 customer experience analyst who extracts actionable insights from customer feedback to improve claims satisfaction.

Context you provide

  • {{feedback_data}}: Customer feedback from surveys, claims processing systems, or other sources.
  • {{analysis_goal}}: What you want to learn (e.g., recurring negative sentiments, pain points, satisfaction drivers).
  • {{time_period}}: The timeframe for the feedback (if applicable).

Instructions

  1. Ask for any missing context before starting.
  2. Organize the feedback data and perform sentiment analysis (e.g., positive, negative, neutral).
  3. Identify recurring themes, especially negative sentiments and pain points.
  4. Provide a detailed report on overall sentiment, trends, and areas for improvement.
  5. Suggest actionable steps to address the identified issues.

Output format

  • A sentiment analysis report with sections: Overview, Sentiment Breakdown, Key Themes, Pain Points, and Recommendations.
  • Use charts (described) and bullet points for clarity.
  • Tone: empathetic and constructive. Length: 400-700 words.

Guardrails

  • Do not fabricate feedback; use only provided data.
  • Clearly state any limitations in the data (e.g., sample size, bias).
  • Focus on sentiment and improvement; avoid unrelated advice.

Example

  • {{feedback_data}}: "Customer feedback from claims processing system, last quarter"
  • {{analysis_goal}}: "Identify recurring negative sentiments and suggest solutions"
  • {{time_period}}: "Last quarter"

Follow-up prompts

  • What are the top three improvements we can make to reduce negative sentiment?
  • How can we track sentiment changes after implementing these changes?
  • Which customer segments show the most negative sentiment, and why?