• ISSN: 2301-3567 (Print), 2972-3981 (Online)
    • Abbreviated Title: J. Econ. Bus. Manag.
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    • DOI: 10.18178/JOEBM
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HOME > Archive > 2026 > Volume 14 Number 1 (2026) >
JOEBM 2026 Vol.14(1): 53-62
DOI: 10.18178/joebm.2026.14.1.909

Small Physical Storefront Attention & Aesthetics Analysis with Neuromarketing Techniques, with AI Latent Display Attributes Tagging for Improvements

S. Liu1, X. Yu1, V. Duvvuri2, R. Chintalapati3, P. Srivastava4, Y. Reddy4 , and A. Jithesh4
1. Northeastern University, San Jose, USA
2. Siriusmindshare LLC, San Jose, USA
3. Electrical Engineering, University of Pennsylvania, Philadelphia, USA
4. San Jose State University, San Jose, USA
Email: liu.sijia2@northeastern.edu (S.L.); yu.xiaohan1@northeastern.edu (X.Y.); venkata@siriusmindshare.com (V.D.); renukac0111@gmail.com (R.C.); pulkit.srivastava@sjsu.edu (P.S.); yashwanthreddykatipally@gmail.com (Y.R.); Aruna.rs.ece@gmail.com (A.J.)
*Corresponding author

Manuscript received December 6, 2025; accepted January 24, 2026; published February 27, 2026.

Abstract—This research explores the role of storefront design in small business marketing, focusing on the challenges and opportunities that small businesses face in optimizing their storefronts. Storefronts are critical, as they represent the first point of contact between a business and potential customers, significantly influencing visibility, foot traffic, brand recognition, and customer acquisition. Despite their importance, many small business owners struggle to create effective storefronts due to limited resources, expertise, and access to advanced marketing tools. As a result, their storefront designs often fail to capture the attention of passersby, particularly in highly competitive retail environments. In recent years, neuromarketing techniques, particularly attention heatmaps derived from eye-tracking studies, have gained prominence for evaluating consumer visual attention and behavior. These techniques, grounded in neuroscientific principles, identify the visual elements that capture the most attention, enabling businesses to improve their storefronts for greater impact. This research applies neuromarketing tools to analyze the visual attention patterns associated with small business storefronts. The study first evaluates the aesthetic and visual quality of these storefronts before applying neuromarketing analysis to assess the attention they attract. Traditional AI models, such as PaQ-2-PiQ and NIMA, are effective at evaluating the overall aesthetic and perceptual quality of images but do not explicitly map attention distribution across storefronts. Neuromarketing outputs, such as heatmaps, provide specific insights into the areas that captivate the viewer’s gaze, allowing for more targeted design improvements. For example, heatmaps can reveal the most visually prominent areas of a storefront, suggesting modifications such as repositioning signage or adjusting color contrasts to increase visibility. One of the significant advantages of this research is its focus on the accessibility of neuromarketing tools for small businesses. Traditional neuromarketing technologies are often costly, but platforms such as Neurons AI offer affordable solutions that provide similar attention insights, making these advanced tools more accessible to smaller enterprises. By integrating image-quality metrics with attention data, small business owners can make data-driven decisions to optimize their storefront designs. The study identifies several key factors that influence attention, such as clear signage, strong branding, and welcoming entrance designs, which correlate with higher attention scores. In contrast, cluttered visuals, poor lighting, and inconsistent branding are identified as common shortcomings that detract from a storefront’s effectiveness. The findings suggest that combining AI-driven quality evaluation with neuromarketing heatmap data provides a comprehensive approach to storefront optimization. In conclusion, the research demonstrates that small businesses can significantly improve the effectiveness of their storefront designs by utilizing neuromarketing insights. When small business owners prioritize attention patterns and aesthetic quality, they can improve the appeal of their storefronts and increase customer engagement, leading to more effective marketing outcomes. This approach empowers small businesses to make informed, actionable design decisions, even with limited resources, resulting in more engaging and effective storefronts.
 
Keywords—Neuromarketing, AI, ML, SMB

Cite: S. Liu, X. Yu, V. Duvvuri, R. Chintalapati, P. Srivastava, Y. Reddy, and A. Jithesh, "Small Physical Storefront Attention & Aesthetics Analysis with Neuromarketing Techniques, with AI Latent Display Attributes Tagging for Improvements," Journal of Economics, Business and Management, vol. 14, no. 1, pp. 53-62, 2026.

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

 
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