Location-Based Tracking Data and Customer Movement Pattern Analysis for Sustainable Fashion Business

Jonghyuk Kim, Hyunwoo Hwangbo, Sung Jun Kim and Soyean Kim
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Jonghyuk Kim: Division of Computer Science and Engineering, Sunmoon University, Tangjeong-meyon, Asan-si, Chungcheongnam-do 31460, Korea
Hyunwoo Hwangbo: Graduate School of Information, Yonsei University, Seoul 03722, Korea
Sung Jun Kim: Department of Civil and Environmental Engineering, Seoul National University, Seoul 08826, Korea
Soyean Kim: Department of International Studies, Kyung Hee University, Yongin-si, Gyeonggi-do 17104, Korea

Sustainability, 2019, vol. 11, issue 22, 1-17

Abstract: Retailers need accurate movement pattern analysis of human-tracking data to maximize the space performance of their stores and to improve the sustainability of their business. However, researchers struggle to precisely measure customers’ movement patterns and their relationships with sales. In this research, we adopt indoor positioning technology, including wireless sensor devices and fingerprinting techniques, to track customers’ movement patterns in a fashion retail store over four months. Specifically, we conducted three field experiments in three different timeframes. In each experiment, we rearranged one element of the visual merchandising display (VMD) to track and compare customer movement patterns before and after the rearrangement. For the analysis, we connected customers’ discrete location data to identify meaningful patterns in customers’ movements. We also used customers’ location and time information to match identified movement pattern data with sales data. After classifying individuals’ movements by time and sequences, we found that stay time in a particular zone had a greater impact on sales than the total stay time in the store. These results challenge previous findings in the literature that suggest that the longer customers stayed in a store, the more they purchase. Further, the results confirmed that effective store rearrangement could change not only customer movement patterns but also overall sales of store zones. This research can be a foundation for various practical applications of tracking data technologies.

Keywords: sustainable fashion business; indoor positioning system; location-based tracking data; spatial analysis; geographic information system; visual merchandising display (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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