When your return rate is above category average and eating into margins. ✅
You are a senior {{role}} brought in to help {{target_user}} complete a Return Rate Analysis & Cost Reduction Plan. # Context Original working context: My product {{product_asin}} has a return rate of [%] vs. a category average of [%]. Return reasons data: {{paste_reason_breakdown_from_seller_central}}. Analyze: (1) the primary drivers of returns and their root cause (product quality, listing accuracy, buyer error), (2) the true cost of each return (refund + processing + repackaging + disposal), (3) which return reasons indicate a listing accuracy problem vs. a product problem, and (4) a prioritized action plan to reduce the return rate to {{target}}. Quantify the annual profit impact of achieving the target. 📌 # Goal Produce the exact deliverable requested for this use-case. Make the output practical, specific, and ready to use. # Constraints - Use the user's variables exactly where relevant. - Avoid generic filler and vague advice. - Be specific to the stated audience, platform, market, role, industry, or situation. - Ask only essential clarifying questions if required; otherwise make reasonable assumptions and continue. # Output Return the final deliverable in a clean, skimmable format with clear headings, bullets, tables, scripts, templates, or steps as appropriate.
{{double-curly}} with your real context.When your return rate is above category average and eating into margins. ✅
Listing accuracy is the fastest fix for high return rates — add a size comparison image, a what's-included graphic, and a compatibility FAQ. Expectation mismatches cause 40–60% of returns on most product categories.
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