Oracle Debuts 'Size Profile Science' for Fashion Retailers

Enterprise software giant Oracle has added 'Size Profile Science' features to its Retail Science Platform Cloud Service; using data science and machine learning to provide fashion retailers with a view of demand for sizes and styles across each store location.

Oracle Retail provides retailers with an integrated suite of business applications, cloud services, and hardware that work together to help fashion, grocery, and specialty retailers anticipate market changes and simplify operations. The new Size Profile Science features have been designed to help fashion retailers maintain and even decrease the inventory levels necessary to drive additional revenue; while increasing customer satisfaction by improving in-stock rates by location. In addition, the features have been developed to ensure optimal sizes are available as required.

For example, using the application, a beachwear retailer would be able to analyze proprietary and third-party customer or consumer-fit datasets to determine what size flip-flops were top sellers in its specific markets. Combining that data with machine learning and artificial intelligence, the company would be able to understand what assortment of sizes would be needed to sell at the top price in each location, and minimize those sizes that would end up on the sale rack. According to Oracle, in a million dollars of inventory, even a five percent reduction in average load would result in $50K in savings, just by putting the right sized products in the right locations at the time of demand.

Jeff Warren (pictured), VP, Oracle Retail, comments: 'Predicting sales at the size and style level, with assortments changing monthly, creates an exorbitant amount of data. Oracle continues to invest in powerful machine learning and artificial intelligence-based applications that enable retailers to quickly turn that data into usable insights and an action plan when it comes to ordering.'

Web site: www.oracle.com .

All articles 2006-23 written and edited by Mel Crowther and/or Nick Thomas, 2024- by Nick Thomas, unless otherwise stated.