Retail and Marketing Analytics

3 credit hours · Undergraduate

Students explore applications of supervised and unsupervised machine learning methods in retail marketing. The focus is on developing retail managerial insights through analytics, without use of programming. Topics include market segmentation, marketing mix modeling, pricing, merchandise planning, customer churn modeling, and demand forecasting. Students work with real-world datasets.