Collecting Consumer Behavior Data with WLAN

Collecting Consumer Behavior Data with WLAN

Patrik Skogster, Varpu Uotila
Copyright: © 2009 |Pages: 16
DOI: 10.4018/978-1-60566-094-3.ch019
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Abstract

Knowing consumers’ shopping paths is an essential part of successful retailing. Good space management requires accurate data about consumer behavior. Traditionally, these data have been collected through, for example, panel interviews, camera tracking, and in-store observation. Their nature is more or less subjective. Modern technology makes it possible to use more objective methods, such as wireless local area network (WLAN) and radio frequency identification (RFID). In this article we examine the possibilities WLAN provides information systems studies. The empirical data is collected from a large DIY (do-it-yourself) store. The results show that WLAN has great potential for accurate and objective data collection processes and modeling data in retailing.
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Literature Review

The consumer buying behavior process inside the store has been studied for several dozens of years. There have been attempts to research it in many different ways. For example, Köhne, Totz, and Wehmeyer (2005) use conjoint analysis, a classical technique, to identify consumer preferences in multi-attribute decision making for designing a new context in sensitive services. They evaluate consumer behavior by using a fictitious example of location-based services in a touristic setting.

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