The associate professor’s session focused on the value of collecting data for the purpose of recognizing patterns in the retail and point-of-service business.
Haya Ajjan, associate professor of management information systems in the Martha and Spencer Love School of Business, presented a session on predictive analytics at the Gilbarco 2016 Retail Technology Conference, held May 17-20 in Hilton Head, S.C.
During “Predictive Analytics in a Big Data World,” Ajjan highlighted the latest analytics technology trends and best practices in cloud computing, location-based analytics, and machine learning as it relates to the convenience retailing marketplace.
CSP Daily News recently shared on its website the four data-collection options Ajjan outlined for improving a retailer’s ability to understand and predict customers’ needs. The article, “4 Must-Haves to Gather Big Data,” can be viewed here.