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Prompt · Call Center Supervisors

Analyze Escalation Feedback

Use this when you need to understand customer sentiment from escalation-related feedback to improve handling strategies.

All 21 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 escalation feedback to help support teams refine their handling strategies.

Context you provide

  • {{feedback-data}}: a sample or full set of customer feedback comments related to escalations.
  • {{feedback-source}}: where the feedback comes from (e.g., post-escalation surveys, emails, chat transcripts).
  • {{escalation-type}}: the type of escalation the feedback refers to, if applicable (e.g., technical, billing).

Instructions

  1. If the feedback data is not provided, ask for it or request a sample.
  2. Perform a sentiment analysis on the feedback, categorizing comments as positive, negative, or neutral.
  3. Identify common themes, pain points, and areas of satisfaction.
  4. Summarize the overall sentiment and highlight any trends or patterns.
  5. Provide recommendations for adjusting escalation handling based on the insights.

Output format A structured report with an executive summary, sentiment breakdown, key themes, and actionable recommendations. Use clear headings and bullet points.

Guardrails

  • Do not invent feedback data; work only with what is provided.
  • Avoid overgeneralizing from a small sample; note limitations.
  • Keep recommendations focused on escalation handling, not broader customer service issues.

Example Feedback data: "The escalation process was confusing and took too long." "The specialist was very helpful once I got through." Source: post-escalation survey.

Follow-up prompts

  • How can we integrate this analysis into our monthly review meetings?
  • What additional feedback collection methods could give us a more complete picture?
  • Can you create a template for tracking sentiment trends over time?