How we helped a Fortune 500 retailer reduce reverse logistics costs by 34% while improving customer satisfaction scores.
The Challenge
Rising returns costs, limited visibility into returns reasons, inefficient disposition processes, and increasing fraud incidents were creating significant margin pressure.
Our Approach
Implemented advanced analytics platform for returns pattern recognition, redesigned authorization workflows, developed ML-based fraud detection, and optimized reverse logistics network routing.
Our client was experiencing escalating costs in their returns process, with limited visibility into root causes and customer behavior patterns. Through a comprehensive data analysis and process mapping initiative, we identified key friction points in the returns journey and implemented targeted interventions across multiple touchpoints. The transformation involved redesigning the returns authorization process, implementing predictive analytics for fraud detection, and creating a dynamic routing system that optimized the disposition of returned items.
The Results
34% reduction in reverse logistics costs, 28% improvement in customer satisfaction scores, 89% fraud detection accuracy, and $12M annual savings realized within the first year.