Estimation of Dominant Attributes of Product for Each Customer through Behavior Observation of Shopping

  • Mika Okuzawa
  • Toshikazu Kato
Part of the Communications in Computer and Information Science book series (CCIS, volume 373)

Abstract

Our purpose is to make a personalized shopping support system in a retail store. In this study, we estimated dominant attributes for each customer through behavior observation of shopping to collecting decision-making data of them with various kinds of products. The dominant attributes are estimated by conjoint analysis of the product attributes and the degree of interest in the product estimated from customer’s behavior. In the experiment with a trial retail store, we achieved success about estimations of 3 of 4 customers. The products recommended by our system also were shown to be better suit for customers.

Keywords

Ubiquitous Sensing Modeling of Customer Preference Smart Shop Online Shop 

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References

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    Ogino, A., Kobayashi, T., Iida, Y., Kato, T.: Smart Store Understanding Consumer’s Preference through Behavior Logs. In: Rau, P.L.P. (ed.) IDGD 2011. LNCS, vol. 6775, pp. 385–392. Springer, Heidelberg (2011)CrossRefGoogle Scholar
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    Yomo, A., et al.: Estimation of Important Attributes of Items in Purchase Process for Personalized Recommendation Service. IPSJ SIG technical reports 2012-HCI-147 (20), 1–8 (2012) (in Japanese) Google Scholar
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    Inoue, K., et al.: Application of Rough Set to Kansei Engineering. Kaibundou, Japan (2009) (in Japanese)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mika Okuzawa
    • 1
  • Toshikazu Kato
    • 2
  1. 1.Graduate School of Science and EngineeringChuo UniversityBunkyo-kuJapan
  2. 2.Faculty of Science and EngineeringChuo UniversityBunkyo-kuJapan

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