How a Fashion Brand Recovered ₹36.9L from Refund & Return Processing Errors
- Category: Fashion & Apparel
- Monthly Amazon Revenue: ₹9.5 Cr
- Number of SKUs: 512
- Fulfillment Model: FBA
- Monthly Returns: ~12,000 Units
Problem
Fashion categories experience significantly higher return rates compared to other product categories.
The brand noticed growing discrepancies between:
- refunds issued to customers
- products returned to the warehouse
- inventory restocked
However, due to the complexity of Amazon’s return processing system, identifying the exact leakage source was extremely difficult.
Discovery
Good Reco analyzed:
- refund transactions
- return status reports
- FBA inventory adjustments
- disposition status logs
The system identified multiple categories of return-related errors, including:
- refunds issued without returns
- returned units marked as lost
- incorrect condition classification
A total of 2,100+ return-related discrepancies were identified.
Action Taken
Good Reco generated structured reimbursement documentation including:
- refund transaction IDs
- return tracking records
- inventory adjustment logs
- condition classification evidence
Claims were submitted through Seller Central across multiple reimbursement categories.
Results
Recovered Amount: ₹36,94,200
Claims Filed: 58
Approval Rate: 89%
Time to Recovery: 82 Days
Breakdown of Recovery:
| Error Type | Amount |
| Refund Without Return | ₹15.2L |
| Incorrect Return Processing | ₹11.8L |
| Lost Returned Inventory | ₹9.9L |
Key Takeaway
High-return categories like fashion require continuous return reconciliation, as small processing errors across thousands of orders can quickly accumulate into large financial losses.