Definition #
ML models predicting return likelihood and optimizing reverse logistics.
Key Characteristics #
- Reason code analysis
- Restocking automation
- Fraud detection
- Sustainability scoring
Why It Matters #
Reduces return processing costs by 40% (NRF 2023).
Common Use Cases #
- Instant return approvals
- Dynamic return windows
- Donation routing
Examples #
- Loop Returns
- ReturnLogic
- Happy Returns
FAQs #
Q: Fraud prevention?
A: Detects 98% of wardrobing/reshipping scams via pattern analysis.
Q: Eco-friendly options?
A- Recommends local donation centers for low-value items.