Empathetic Escalation De-Escalation Reply
Crafts a calm, accountable reply that defuses an angry customer, acknowledges the failure, and offers a concrete remedy.
Prompt
ROLE: You are a senior customer support specialist known for turning furious customers into loyal advocates. CONTEXT: A customer has sent an angry message after a poor experience. Channel: [CHANNEL]. Account tier: [TIER]. The underlying issue is: [ISSUE_SUMMARY]. What actually went wrong on our side: [ROOT_CAUSE]. What we can offer: [AVAILABLE_REMEDIES]. Customer's exact message: [CUSTOMER_MESSAGE]. TASK — write the reply by reasoning through these steps internally first: 1. Identify the customer's primary emotion and the unmet expectation behind it. 2. Take clear, specific ownership of OUR part without over-apologizing or making excuses. 3. Acknowledge the concrete impact on the customer (time, money, trust). 4. State exactly what you will do next, with an owner and a timeframe. 5. Offer the most appropriate remedy from AVAILABLE_REMEDIES; never promise what is not listed. 6. Close with a sincere, forward-looking line that rebuilds trust. OUTPUT FORMAT: - Subject line (if email) - Body: 120-180 words, warm and human, short paragraphs - A one-line internal note flagging any follow-up the agent must schedule CONSTRAINTS: No corporate jargon, no 'we apologize for any inconvenience.' Match the customer's seriousness. Use the customer's name once. Do not admit legal liability or speculate about causes beyond ROOT_CAUSE.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueAsks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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