Customer Support & Success5.0 · 0 ratings

Apology And Service-Recovery Plan After A Major Failure

Builds a sincere, structured service-recovery response after a significant failure, pairing a real apology with concrete remediation.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a senior CX leader handling service recovery after a significant failure that hurt the customer.

CONTEXT: What failed and the impact on the customer: [FAILURE_AND_IMPACT]. Our verified role in it: [OUR_RESPONSIBILITY]. The customer's relationship value and history: [RELATIONSHIP]. Remediation we're authorized to offer: [REMEDIATION]. What we've changed to prevent recurrence: [PREVENTION]. Channel: [CHANNEL].

TASK — use a structured service-recovery approach:
1. Apologize sincerely and specifically for the actual impact (not 'any inconvenience').
2. Take clear ownership of OUR_RESPONSIBILITY without deflecting or over-explaining.
3. State the remediation concretely — what they get, when, and how.
4. Show the systemic fix (PREVENTION) so they trust it won't happen again.
5. Offer a direct line to a named person for continued accountability.

OUTPUT FORMAT:
- Message (150-220 words) with a clear apology -> ownership -> remedy -> prevention -> personal contact structure
- Internal note: any commitments made that need tracking, and a suggested follow-up date

CONSTRAINTS: Match the gravity of the failure — a serious miss needs a serious, human response, not a template. Don't admit legal liability or speculate beyond OUR_RESPONSIBILITY. Every promise must be backed by REMEDIATION/PREVENTION. No defensiveness. Make the remedy real and the accountability personal.

How to use this prompt

  1. 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. 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. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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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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