Reducing Chargebacks for a Global Fashion Retailer
Developed a predictive model for a global fashion retailer, reducing chargeback costs by $130,000 annually and improving execution efficiency by 90%. This AI-driven solution enhanced risk detection, streamlined supply chain operations, and boosted partner trust through proactive issue mitigation.
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Challenge
A global fashion retailer, known for its contemporary and casual collections, faced recurring chargebacks stemming from delayed or incomplete wholesale order fulfillment. These chargebacks were costing the company over $2 million annually, highlighting the need for a proactive approach to mitigate fulfillment risks and improve supply chain efficiency.
Solution
The retailer collaborated with v4c.ai and Dataiku to develop a predictive model capable of identifying at-risk orders before delays or partial fulfillment occurred. The solution provided:
- Early Risk Detection: Pinpointed wholesale orders at risk of delay or incomplete fulfillment.
- Proactive Mitigation: Enabled the team to address potential issues in real time, reducing operational bottlenecks.
Impact
The implementation of this solution delivered measurable results:
- $130,000 Annual Savings: A significant reduction in chargeback costs, directly improving the retailer's bottom line.
- 90% Execution Efficiency: Streamlined workflows and minimized delays, ensuring smoother operations.
- +75% Recall Accuracy: The model's precision enhanced the team's ability to anticipate and address fulfillment issues proactively.
This data-driven approach transformed the retailer's supply chain management, reducing costs, improving operational agility, and reinforcing trust with wholesale partners.
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