Case Study: Leading U.S.-Based Online Retailer of Automotive Parts and Accessories achieves profitable private-label product selection with Cybage Software

Leading U.S. Based Online Retailer Of Automotive Parts and Accessories - Customer Case Study

The Leading U.S. Based Online Retailer Of Automotive Parts and Accessories, a U.S.-based online seller of more than 550,000 automotive parts and accessories across its own site and major marketplaces, needed a better way to identify private-label candidates. Working with Cybage Software and its DecisionMines™ prescriptive retail solution, the retailer sought to replace conservative, manual product selection with a data-driven method for predicting which SKUs would be most profitable over the next few months.

Cybage Software built an actionable dashboard using data from product, sales, web analytics, demand, competition, and vehicle-in-operation sources to rank products by private-label potential. Using Naïve Bayes and Bucketizer models, the solution classified SKUs into the top 3% of likely best performers, helping the client launch products like rear view and side view mirrors. The business impact included 8–10% lower prices than competitors, 20–25% higher profit margins, and a 15% revenue share within one year of launch.