Optimal Pricing and Promotion Strategies in IT-Enabled Retail Environment

Abstract

The emergence of retail technologies and analytics has drastically changed the retail industry landscape. This thesis focuses on two technologies: Location-Based Service (LBS) and Customer Relationship Management (CRM) Systems; and studies their economic impact on pricing, promotion and competitive strategies. Study 1 presents an analytical study on optimal pricing and adoption strategy with LBS. The results show that in the optimal strategy for LBS infomediary as a coupon delivery channel, retailers either adopt or reject LBS together, depending on the size of uninformed segments and reach of LBS. Study 2 presents an empirical approach to determine the optimal pricing and promotion strategies with behavioral-based segmentation. By analyzing the data from the CRM Systems of a fashion retailer, we develop a customer profitability model and segmentation strategy based on consumer demographics and behavioral-based characteristics using the finite-fixture model. The results provides key implication on the profit impact of pricing and promotion.