Case Study: Largest U.S. Distributor of Plumbing Supplier achieves 95% product classification accuracy with Tredence's Sancus

Used Sancus to Help a Leading Industrial Company Get Better Visibility Into Revenue and Sales Opportunity

Tredence helped the largest U.S. distributor of plumbing supplies, PVF, waterworks, fire and fabrication products tackle a major product classification challenge. The customer had nearly 3 million SKUs that needed to be assigned to product families, but only about 30,000 had been manually classified, making the process slow and inefficient.

Using Sancus, Tredence built an automated classification solution that combined data engineering, text mining, and neural network-based machine learning, then deployed it on Microsoft Azure. The result was a 28x increase in monthly classification throughput and product classification accuracy improved to 95%, giving the customer better visibility into revenue and sales opportunities by product category.