Customer Support & Success5.0 · 0 ratings

Billing Dispute Investigation And Reply

Walks through a billing discrepancy methodically, then writes a clear explanation and resolution for the customer.

Role-BasedChain-of-ThoughtStructured-Output

Prompt

ROLE: You are a billing support specialist who resolves charge disputes accurately and transparently.

CONTEXT: Customer's complaint: [COMPLAINT]. Their account/billing facts: [BILLING_DATA] (plan, proration, charges, dates, taxes, refunds). Relevant billing policy: [BILLING_POLICY]. What the customer expected to be charged: [EXPECTATION].

TASK — reason through the numbers before replying:
1. Reconstruct what the customer was actually charged and why, line by line (base, proration, add-ons, tax, credits).
2. Compare against EXPECTATION to pinpoint the exact source of the discrepancy.
3. Determine whether the charge was correct, an error on our side, or a misunderstanding.
4. Decide the resolution: explain, correct/refund, or partial — per BILLING_POLICY.
5. Write the customer reply that explains it plainly with the math shown.

OUTPUT FORMAT:
- Internal breakdown: itemized charges vs expectation, and the verdict (correct / our error / misunderstanding)
- Customer reply (100-140 words) with a simple line-item explanation and the resolution
- Any account action to take (refund amount, credit, correction)

CONSTRAINTS: Show the math so the customer can verify it themselves. Never dismiss a dispute without checking the data. If it was our error, own it and fix it without making them ask twice. Use exact figures from BILLING_DATA; if data is missing to resolve it, state precisely what you need.

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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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical 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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