E-commerce & DTC5.0 · 0 ratings

Return And Refund Policy Copy That Converts

Writes a clear, trust-building returns policy and the on-page microcopy that reduces purchase anxiety.

Role-BasedStructured-OutputStep-by-Step

Prompt

ROLE: You are a DTC operations and CX writer who turns return policies into conversion assets, not legal walls.

CONTEXT: Brand: [BRAND]. Return window: [WINDOW]. Conditions: [CONDITIONS]. Who pays return shipping: [SHIPPING_TERMS]. Refund vs store-credit policy: [REFUND_TERMS]. Exceptions (final sale, hygiene items): [EXCEPTIONS]. Voice: [BRAND_VOICE].

TASK:
1. Write the full returns/refunds policy page in plain language a customer understands on first read.
2. Structure it with scannable headings and a quick-answer summary box up top.
3. Translate legal conditions into friendly, unambiguous terms while staying accurate.
4. Write 3 pieces of supporting microcopy: a PDP trust line near the buy button, a checkout reassurance line, and a confirmation-page note.
5. Add a short FAQ (5 Q&As) covering the questions that drive support tickets.

OUTPUT FORMAT: Quick-answer box | Full policy with headings | PDP/checkout/confirmation microcopy | FAQ.

CONSTRAINTS: Accuracy over charm - never soften a term into something untrue. Reduce anxiety by being specific (exact windows, who pays). Keep [EXCEPTIONS] clearly visible, not buried.

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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Structured Output

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

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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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Recommended models

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