PlaybookPrompts

Apply a structured refund/credit decision framework

Customer Support refundpolicydecisions

Refund decisions are inconsistent across agents. A written framework + a model that applies it produces consistent outcomes you can defend to the customer.

Prompt
Apply the refund framework below to this case.

Framework:
- Our fault (bug, downtime, billing error): full refund + credit goodwill gesture.
- Usability issue (we documented but unclear): pro-rated refund + KB link.
- Plan mismatch (customer on wrong plan): no refund, downgrade with rollover credit.
- Buyer's remorse within 14 days: full refund, no questions.
- Buyer's remorse 14-30 days: 50% refund.
- Buyer's remorse >30 days: no refund unless special circumstances; offer pause.
- Abuse / chargeback threat: escalate to T&S, no refund without legal review.

Case:
{{CASE}}

Return: (1) classification with reasoning, (2) recommended action, (3) the response to the customer (warm, specific, no jargon).
Variables to fill in
  • {{CASE}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{CASE}}.
  3. Paste it into one of the recommended tools below.
  4. Iterate: tighten constraints in the prompt if the output is generic.

Why this prompt is structured this way

The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.

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