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Analyzing Customer Behavior In-Store: A Review of Available Technologies

In: Advances in Digital Marketing and eCommerce

Author

Listed:
  • Olaf Saßnick

    (Salzburg University of Applied Sciences)

  • Robert Zniva

    (Salzburg University of Applied Sciences)

  • Christina Schlager

    (Salzburg University of Applied Sciences)

  • Matthäus Horn

    (Salzburg University of Applied Sciences)

  • Reuf Kozlica

    (Salzburg University of Applied Sciences)

  • Tina Neureiter

    (Salzburg University of Applied Sciences)

  • Simon Kranzer

    (Salzburg University of Applied Sciences)

  • Viktoria Müllner

    (Salzburg University of Applied Sciences)

  • Julian Nöbauer

    (Salzburg University of Applied Sciences)

Abstract

Online channels collect almost effortlessly a lot of behavioral customer data in a fully automated manner. Providing a comparable number of metrics for traditional brick-and-mortar environments is challenging and requires the introduction of additional sensor technology. In this work a systematic computer science literature review is carried out to provide an overview of measurement objects, associated characteristics, and sensor technologies for brick-and-mortar retail environments. The measurement objects can be divided into product and person detection, with the latter focusing on determining the characteristics of persons, namely frequency, path, and features. From the identified sensor technologies, image and depth sensors are the most versatile, but also require the highest computational effort and infrastructure cost. For the detection of some characteristics, other technologies, like wireless beacons, provide a viable alternative. Results are presented in a suitability matrix. Based on the results we propose a stronger interdisciplinary collaboration between marketing and computer science scholars.

Suggested Citation

  • Olaf Saßnick & Robert Zniva & Christina Schlager & Matthäus Horn & Reuf Kozlica & Tina Neureiter & Simon Kranzer & Viktoria Müllner & Julian Nöbauer, 2023. "Analyzing Customer Behavior In-Store: A Review of Available Technologies," Springer Proceedings in Business and Economics, in: Francisco J. Martínez-López (ed.), Advances in Digital Marketing and eCommerce, pages 243-252, Springer.
    • Handle: RePEc:spr:prbchp:978-3-031-31836-8_25
    DOI: 10.1007/978-3-031-31836-8_25
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