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In-Store Journey Model with Purchasing Behavior Based on In-Store Journey Data and ID-POS Data

Author

Listed:
  • Yutaro Ishimaru

    (Osaka Prefecture University)

  • Hiroyuki Morita

    (Osaka Prefecture University)

  • Yusuke Goto

    (Iwate Prefecture University Iwate)

Abstract

ID-POS data have been analyzed in many retail stores for several decades, and the results have been used to support decision-making such as sales promotion and item arrangement in the stores. Such analysis affects various business performance like total sales. Although the data are so useful, it is difficult to grasp the extent of customer’s interest in items that were not purchased and to identify that it is a planned purchase or not. Therefore, we need to use in-store customer journey data to reveal that complementary. In this paper, we propose an in-store journey simulation model with purchasing behavior and carry out the agent-based simulation using actual in-store customer journey data acquired using the Bluetooth beacons and ID-POS data. From several computational experiments, we show that our model reproduces actual in-store customer journey and purchasing behavior, and we evaluate our model from the viewpoint of the difference between our results and the actual data. Finally, we predict the effect on a sales promotion using the proposed model and agent-based simulation.

Suggested Citation

  • Yutaro Ishimaru & Hiroyuki Morita & Yusuke Goto, 2021. "In-Store Journey Model with Purchasing Behavior Based on In-Store Journey Data and ID-POS Data," The Review of Socionetwork Strategies, Springer, vol. 15(1), pages 215-237, June.
    • Handle: RePEc:spr:trosos:v:15:y:2021:i:1:d:10.1007_s12626-021-00078-5
    DOI: 10.1007/s12626-021-00078-5
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    Citations

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    Cited by:

    1. Taizo Horikomi & Takayuki Mizuno, 2024. "Generating in-store customer journeys from scratch with GPT architectures," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(9), pages 1-9, September.
    2. Taizo Horikomi & Mariko I. Ito & Takaaki Ohnishi, 2022. "ID-POS Data Analysis Using TV Commercial Viewership Data," The Review of Socionetwork Strategies, Springer, vol. 16(2), pages 431-451, October.

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