Customer modeling method constructed from behavioral data and lifestyle survey

Hitoshi Koshiba, Tsukasa Ishigaki, Takeshi Takenaka, Eeichi Sakurai, Yoichi Motomura

研究成果: Article査読

1 被引用数 (Scopus)


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.

ジャーナルIEEJ Transactions on Electronics, Information and Systems
出版ステータスPublished - 2013

ASJC Scopus subject areas

  • 電子工学および電気工学


「Customer modeling method constructed from behavioral data and lifestyle survey」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。