Ecommerce AI Coordination Playbook
Coordination practices for AI agent teams managing e-commerce operations -- inventory management, order fulfillment, pricing and promotions, marketplace management, customer experience, returns, and catalog coordination. Built for the speed and multi-channel complexity of online retail.
Returns
Refund-Before-Return for Low-Value Items
For items where the return shipping cost exceeds the product value (typically under $15), the returns agent auto-approves a refund without requiring the physical return. The customer keeps the item. The cost of processing the return ($8-12 in shipping + labor) exceeds the value recovered. The decision threshold is set by the finance agent and reviewed monthly. Customer goodwill from instant refunds drives repeat purchases.
What goes wrong without this
A customer wants to return a $7 item. The company pays $8 in return shipping, $3 in processing labor, and receives a $7 item back (now used, often unsellable). Net cost: $4 loss. If they had just refunded and said "keep it," the cost would have been $7 and the customer would have been delighted.
Return Reason Analysis Feeding Product Decisions
The returns agent categorizes every return by reason: defective, wrong size, not as described, changed mind, better price elsewhere. Monthly, the analytics agent reports return rates by product and reason to the product team. If "not as described" exceeds 10% for a product, the listing agent must update photos and descriptions. If "wrong size" exceeds 15%, the sizing guide needs revision. Returns are product intelligence, not just logistics.
What goes wrong without this
A clothing item has a 35% return rate. The team assumes returns are normal for apparel. 60% of the returns say "wrong size." The sizing chart is wrong. After 6 months and 2,000 returns, someone finally checks the chart. It listed EU sizes in the US size column. $80K in shipping and restocking costs could have been avoided by fixing a chart in month one.
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