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Evaluating exposure of a retail rack layout in 3D

  • Bradley Guthrie
  • Pratik J. ParikhEmail author
Article
  • 4 Downloads

Abstract

Analyzing a retail layout accounting for how a shopper visually interacts with racks along their shopping path can help the retailer identify hot-warm-cold spots and better allocate products to racks in order to maximize revenue. We focus on estimating exposure (which locations are likely to be seen) and the intensity of exposure (how long are they seen) by accounting for the dynamic interaction between the human 3D field of regard with a physical rack layout. Our quantitative approach allows us to analyze the effect of varying layout design parameters (i.e., rack orientation, curvature, and height) on exposure considering both unidirectional and bidirectional travel. We also validate our approach through human participants in a virtual layout. We observed that curving racks in a layout with racks oriented 90° (i.e., perpendicular to the aisle) increase exposure by 3–121% over straight racks. Further, orientating curved racks at acute angles leads to substantially higher exposure (18–321%) over straight racks at 90°. Moreover, racks with a height just below shopper eye-height results in higher exposure over racks just above eye-height when top surfaces are accounted for as exposed. Considering the trade-off between exposure and layout floor space, when given an allowable 25% increase in floor space, we found feasible layouts that increased exposure ranging from 15–530% (over straight racks at 90°) depending on shopper scanning pattern, layout size, and traffic direction.

Keywords

Retail layout Exposure Field of vision Quantitative model 

Notes

Acknowledgements

This research was supported in part by the US National Science Foundation under grant CMMI #1548394. We acknowledge the help of our collaborators in Computer Science (Thomas Wischgoll and Madison Glines) and Psychology (John Flach, Scott Watamaniuk, and Tyler Whitlock) at WSU during the human subjects study.

Supplementary material

10696_2019_9368_MOESM1_ESM.pdf (1 mb)
Supplementary material 1 (PDF 1039 kb)
10696_2019_9368_MOESM2_ESM.pdf (543 kb)
Supplementary material 2 (PDF 543 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Biomedical, Industrial and Human Factors EngineeringWright State UniversityDaytonUSA

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