ردیابی رفتار مشتری در روش خرده فروشی با استفاده از RFID Tracking customer behaviour in fashion retail using RFID

INTRODUCTION In today’s business environment, fashion retailers face multiple challenges, most of which are related to the expansion into and balancing of omni-channel retailing. Customers are more informed than before, and the transaction cost of comparing and switching between both online and brick and mortar retailers is decreasing (Nunes and Cespedes, 2003, Stone et al., 2002). Physical stores have traditionally played the advantage of enabling product ‘touch and feel’, correct fit and sizing, zero delivery lead-time, and advice and up-sales from sales representatives (Bhatnagar et al., 2000, Liao and Cheung, 2001, Levin et al., 2003). However, the lines between online and offline retail are fading (Enders and Jelassi, 2000). Online channels increasingly offer free returns, next or same day shipping and improved choice navigation aiding the customers, while benefiting from advantages such as consolidated inventory, economies of scale in purchasing and lower labour and facilities costs. In order to remain attractive and economically viable, physical stores need to operate as efficient as possible and, at the same time, excite customers in innovative ways. Under these conditions of modern retail, being able to detect and understand customer behaviour may constitute a competitive advantage. Ultimately, the retailer would like to know everything about the customer the minute he or she enters the store, in order to tailor a marketing message to the individual needs and beliefs of the customer and the nature of the selling situation. In online shopping, retailers generally have access to large amounts of log files and data-rich customer profiles through tracking cookies and analytics. However, such information is rarely available for physical stores. Instead, the retailer needs to categorize customers based on certain characteristics and serve them accordingly (Dodd et al., 1998). Customer segmentation has received significant attention in the quest for competitive advantage (Lewis and Hawksley, 1990), and research on the subject has a long history going back around 60 years (Van Vliet, 2014). Over the last three decades, customer segmentation has turned from macro-level (market characteristics such as demographical descriptions) to more micro-level (with focus on individual customers). This has led to increased attention to in-store behaviour mapping, to increase the understanding of the customers.