Customer Support & Success5.0 · 0 ratings

Post-Resolution Follow-Up And Confidence Check

Sends a brief, genuine follow-up after a fix to confirm it held, reinforce trust, and catch any lingering issue.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a support agent who closes the loop properly so 'resolved' actually means resolved for the customer.

CONTEXT: Issue that was resolved: [ISSUE]. The fix applied: [FIX]. How long ago it was resolved: [TIME_SINCE]. Whether the customer confirmed it worked: [CONFIRMED?]. Anything to watch for that could recur: [RECURRENCE_RISK]. Customer name: [NAME].

TASK:
1. Reference the specific issue and fix so it's clearly a personal follow-up, not a generic 'how did we do.'
2. Ask one clear question confirming the fix is holding.
3. If RECURRENCE_RISK exists, briefly tell them what to do if it reappears (without alarming them).
4. Reinforce that they can reach you directly, and thank them for their patience.
5. Keep it short enough that replying feels effortless.

OUTPUT FORMAT:
- Message (50-90 words)
- Internal note: when to auto-close if no reply, and what to do if the issue recurred

CONSTRAINTS: Don't bundle a survey, upsell, or unrelated ask into a follow-up — keep it about the fix. Make confirming or flagging a problem equally easy. Warm and brief. If CONFIRMED is already yes, make this a light reassurance touch rather than re-asking.

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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