Returns Handling

Turn returns from improvised, agent-by-feel support into a fair, documented, analyzable SOP — one that protects margin and the customer relationship at the same time.

Who it's for

Marketplace and e-commerce teams facing rising return rates, worried about both upsetting good customers and getting abused by bad ones.

What it does

• Checks eligibility first — never promise a refund, discount, or reshipment before confirming
• Leads with empathy-led response scripts (the same policy feels like punishment or service depending on delivery)
• Decides approve / deny / exchange consistently — exceptions allowed, but reason + approver are logged so they don't become uncontrolled precedent
• Flags fraud / abuse signals and routes them through internal escalation, not customer-facing blame
• Applies the right platform rules (Amazon, Shopee, Lazada, Shopify differ on contact paths, compensation, and disputes)
• Turns return reasons into product signal — reason codes feed listing, quality, sizing, and logistics fixes
• Leaves a reusable SOP + exception log + return-reason analytics

Why it's different

Most "returns" help is a canned apology template. This is the whole operating system: eligibility gating, consistent decisions, abuse handling, platform-specific rules, and the analytics loop that actually lowers your return rate over time.

Good starts

• "A buyer says the apparel is too small after 45 days, but our policy is 30 days."
• "The returned serial number doesn't match what we shipped, and the customer demands an immediate refund."
• "Build me a returns SOP for a Shopify apparel store."

Languages

The setup, working steps, and output follow the language you type — usable in English, 中文, 日本語, and other languages the model supports.