Partner Character Attracting Consumers to a Real Store

  • Motoi Okuzono
  • Masahumi Muta
  • Soh Masuko
  • Hayaki Kawata
  • Junichi Hoshino
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10507)

Abstract

The diversification of personal tastes and the rapid increase in choices makes it difficult to select things that suits them. For service providers it is fixedly segmented like a conventional mass media It is becoming more difficult to provide advertisements and services to individuals. Because of these circumstances, it is requested that we can accurately acquire personal preferences and analyze them. On the other hand, attention is focused on O2O, which connects online actions to offline online shopping in real stores.We also use gaming which makes various elements of everyday life into a game, Measures have also been taken to immerse and positively tackle purchasing behavior. In the marketing field, it is said that narrative is important for inducing user’s behavior. Therefore, in this research, we construct a partner character system based on scenario game and verify whether we can increase purchasing behavior in a real shop by making users engage in the system using scenarios and characters that can be friends with users.

Keywords

Pertner character O2O Gamification 

References

  1. 1.
    Shankar, A., Elliott, R., Goulding, C.: Understanding consumption: contributions from a narrative perspective. J. Mark. Manag. 17(3-4), 429–453 (2001)Google Scholar
  2. 2.
    Book of kind of breads | COOKTWON. https://papatto-cooktown.jp/contents/kind_of_bread. 10 Apr 2017

Copyright information

© IFIP International Federation for Information Processing 2017

Authors and Affiliations

  • Motoi Okuzono
    • 1
  • Masahumi Muta
    • 2
  • Soh Masuko
    • 2
  • Hayaki Kawata
    • 1
  • Junichi Hoshino
    • 1
  1. 1.Graduate School of Systems and Information EngineeringUniversity of TsukubaTsukuba-shiJapan
  2. 2.Rakuten, Inc., Rakuten Institute of TechnologySetagaya-kuJapan

Personalised recommendations