Estimating customer preference through store check-in histories and its use in visitor promotion

Chiaki Doi, Masaji Katagiri, Akira Ishii, Teppei Konishi, Takashi Araki, Ken Ohta, Daizo Ikeda, Hiroshi Inamura, Hiroshi Shigeno

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper proposes a method to estimate the preference of customers based on store check-in histories. The proposed method can distinguish the preferences of customers who have no purchase histories. We adopt a machine learning algorithm for model acquisition. The estimation results can improve the efficiency of visitor promotion campaigns and advertising campaigns. An actual visitor promotion trial indicates the effectiveness of the proposed method.

Original languageEnglish
Title of host publication2017 10th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9784907626310
DOIs
Publication statusPublished - 2018 Apr 2
Event10th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2017 - Toyama, Japan
Duration: 2017 Oct 32017 Oct 5

Publication series

Name2017 10th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2017
Volume2018-January

Other

Other10th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2017
Country/TerritoryJapan
CityToyama
Period17/10/317/10/5

Keywords

  • Check-in History
  • Customer preference
  • Promotion
  • Purchase History

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Safety, Risk, Reliability and Quality

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