A data mining-based framework to identify shoppers’ missions

Abstract

Consumers' behavior and expectations for service have changed dramatically in recent years, as they have become more demanding. Many organizations have identified the need to become more customer centric, facing increased global competition (Bull, 2003; Phan & Vogel, 2010). Therefore, in order to respond to the ever increasing demands of consumers, they are trying to develop innovative methods for managing their customers (Anderson et al., 2007). At the same time computers have become far more powerful, and new technological trends have been developed, such as Big Data, Business Intelligence (BI), Data Mining (DM) (Provost & Fawcett, 2013). These new trends give us the opportunity to process large volumes of data and extract valuable information. Like any other business, so do retailers have realized the importance of applying these new technological trends to support decision making and satisfy their customers (Bertino, 2011). However, there is only sparse research in the context of retailing in order to discover patterns in customers' behavior, to empower decision making, and to satisfy the demanding consumers (Wang & Zhou, 2013).