Case Study: a global B2B marketplace improves bid win rate with Ugam machine learning automation

Global B2B Marketplace - Customer Case Study

The customer, a global B2B marketplace, was facing challenges with its manual bid response process. This process was inefficient and error-prone, unable to keep up with the company's rapid growth and the resulting volume of complex bid requests. Their key objective was to increase their win rate by offering the lowest possible prices. They partnered with vendor Ugam to implement its machine learning-based solution for bid response automation.

Ugam's machine learning algorithms automated the bid response process by accurately matching products, normalizing units of measure, and identifying the lowest-priced product alternatives. This allowed the client to quickly determine the most competitive prices for a high volume of SKUs across multiple categories. As a result, the global B2B marketplace saw its win rate improve by close to 10% within just two quarters of implementation.