Issue No. 01 - Jan.-Mar. (2014 vol. 13)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MPRV.2013.24
Chuang-Wen You , Research Center for Information Technology Innovation
Hsin-Liu Cindy Kao , National Taiwan University
Bo-Jhang Ho , National Taiwan University
Yu-Han Tiffany Chen , Massachusetts Institute of Technology
Wei-Fehng Wang , National ChengChi University
Lien-Ti Bei , National ChengChi University
Hao-Hua Chu , National Taiwan University
Ming-Syan Chen , Research Center for Information Technology Innovation
Systematically and quantitatively determining patterns in consumer flow is an important problem in marketing research. Identifying these patterns can facilitate an understanding of where and when consumers purchase products and services at physical retail shops. Collecting data on real consumers who shop at retail stores is one of the most challenging and expensive aspects of these studies. This article introduces ConvenienceProbe, a phone-based data collection system for retail trade-area analysis. The proposed method targets local residents shopping at neighborhood convenience stores. This study deploys and tests the system by collecting real customer flow data in neighborhood convenience stores. Results show that the consumer flow data collected from the ConvenienceProbe system is comparable to that from a traditional face-to-face interview method.
Sales and marketing, Pattern recognition, Consumer behavior, Marketing and sales, Sensors, Behavioral science, Data processing
C. You et al., "ConvenienceProbe: A Phone-Based System for Retail Trade-Area Analysis," in IEEE Pervasive Computing, vol. 13, no. 1, pp. 64-71, 2014.