Return Policy Generator for Singapore Ecommerce Sellers

Quick way to use this tool

This Return policy generator is intentionally built as a prompt builder. It does not pretend to run a hidden model on this page. Instead, it turns your inputs into a structured prompt with role, context, task, output format, constraints, quality check, follow-up prompt, copy buttons, and a review checklist. That makes the page useful while keeping the actual drafting step in your own AI tool. After you build the prompt, paste it into your preferred AI tool and treat the answer as a draft that still needs human review.

Start with the smallest useful scenario. For example, use one product instead of a whole catalog, one role instead of a whole team, one policy instead of an entire legal page, or one gateway setup instead of every payment method at once. That keeps the output clear enough to compare with your real numbers and constraints.

What the inputs mean

• Product category: replace the default with the value that matches the exact scenario you are checking. Category affects return rules.
• Return window: replace the default with the value that matches the exact scenario you are checking. Use your intended policy.
• Exceptions: replace the default with the value that matches the exact scenario you are checking. List exclusions clearly.

The defaults are examples, not benchmarks. Replace them before you make a decision. If you do not know an input yet, use the closest conservative estimate and write down the assumption beside the result. That way you can rerun the Return policy generator later when you have better data.

How to interpret the output

A good prompt-builder result should be specific enough to guide the AI tool, but constrained enough to stop it from inventing facts. Before using the AI answer, check every claim, remove unsupported promises, replace generic language, and adapt the output to the channel where it will appear. If the answer sounds polished but vague, run the follow-up prompt and ask for concrete edits.

Do not treat the first output as final advice. Compare it with your store data, marketplace dashboard, rate card, supplier quote, customer support logs, campaign report, contract, or policy document. If the tool exposes a weak point, fix that weak point before optimizing details that have less impact.

Common mistakes to avoid

• Using blended averages when one product, courier lane, role, or channel behaves very differently.
• Copying the result into a decision without checking current platform, tax, fee, courier, or policy rules.
• Treating a clean-looking number or prompt as proof that the underlying business assumption is sound.
• Forgetting to rerun the tool after a supplier, marketplace, payment provider, ad platform, courier, or policy change.

Before you act

For legal, tax, registration, and compliance topics, use the result as an educational planning aid only. Local rules, thresholds, filing duties, consumer protection requirements, and platform policies can change. Before relying on the result, confirm the current rule with the relevant official source or a qualified professional.

Save the result with the date, input assumptions, and the decision you made. If the decision matters to margin, compliance, customer experience, or hiring quality, review it again after real data comes in. The value of a free tool is not the first number or prompt. The value is making the assumption visible so you can improve it.