It becomes increasingly important for service industries to understand customer behavior using large-scale data such as POS data. However, limitations exist in a customer model constructed on the basis of such behavioral data alone. This paper presents how we can construct a customer model on the basis of both large-scale purchase data and lifestyle survey data. It proposes a method that reveals the connection between lifestyle and behavior by deducing lifestyle from behavioral data using Random Forests, a machine learning algorithm. Then, It applies the proposed method to an actual mass merchandizers using questionnaires on lifestyle collected and the customer behavioral data (ID-POS Data). It thereby demonstrates the effectiveness of the proposed method and its possible use in supporting managerial decision-making on critical issues such as product selection. ©2013 The Institute of Electrical Engineers of Japan.
CITATION STYLE
Koshiba, H., Ishigaki, T., Takenaka, T., Sakurai, E., & Motomura, Y. (2013). Customer modeling method constructed from behavioral data and lifestyle survey. IEEJ Transactions on Electronics, Information and Systems, 133(9). https://doi.org/10.1541/ieejeiss.133.1787
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