SURVEY ON RETAIL INSIGHT GENERATOR: VISION AI FOR CUSTOMER ANALYTICS AND HEATMAPS
Abstract & Details
Research Area
Computer Engineering
Keywords
Retail Analytics
Artificial Intelligence (AI)
Computer Vision
Deep Learning
Convolutional Neural Networks (CNN)
YOLO (You Only Look Once)
Object Detection
Multi-Object Tracking
Customer Behavior Analysis
Heatmap Generation
Footfall Analysis
Dwell Time Estimation
Demographic Analysis
Real-Time Video Processing
Vision AI
Retail Intelligence
Smart Surveillance
Data-Driven Decision Making
Store Optimization
AI Strategy Engine.
Abstract
The rapid evolution of retail environments has intensified the need for intelligent systems capable of understanding customer behavior and optimizing in-store operations. Traditional retail analytics methods often lack real-time insights and detailed behavioral tracking, limiting their effectiveness in data-driven decision-making. This study presents a Vision AI-based Retail Insight Generator that leverages advanced computer vision and deep learning techniques—specifically Convolutional Neural Networks (CNNs) and real-time object detection models such as YOLO—to analyze customer activity from video streams. The proposed system is designed to detect, track, and analyze customers within retail spaces, extracting meaningful insights such as footfall distribution, dwell time, movement patterns, and demographic attributes including age and gender. The architecture follows a structured pipeline consisting of video preprocessing, human detection and tracking, feature extraction, and analytics generation. Additionally, the system incorporates heatmap visualization to identify high-engagement zones and an AI-driven strategy engine that provides actionable business recommendations based on observed patterns. To enhance decision-making capabilities, the system includes modules for real-time monitoring, historical trend analysis, and hourly engagement evaluation, enabling retailers to understand customer behavior across both temporal and spatial dimensions. The integration of analytics with an interactive dashboard ensures intuitive visualization and efficient interpretation of complex data. By transforming raw video data into actionable intelligence, the proposed system significantly reduces manual effort and enhances operational efficiency. It is particularly beneficial for retail environments with limited access to advanced analytical tools, providing a scalable and cost-effective solution. The results demonstrate that AI-assisted retail analytics systems can play a crucial role in improving customer experience, optimizing store layouts, and driving strategic business growth. This study highlights the potential of Vision AI as a transformative technology in modern retail analytics and intelligent decision-support systems.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Amalkrishna K B | Holy Grace Academy of Engineering |
| 2 | Hariprasad PS | Holy Grace Academy of Engineering |
| 3 | Edwin Davis P | Holy Grace Academy of Engineering |
| 4 | Ahmed Razal | Holy Grace Academy of Engineering |
How to Cite
Use the following formats to cite this article in your research.
APA Style
B, Amalkrishna K, PS, Hariprasad, P, Edwin Davis, & Razal, Ahmed (2026). SURVEY ON RETAIL INSIGHT GENERATOR: VISION AI FOR CUSTOMER ANALYTICS AND HEATMAPS. International Journal of Advance Research and Innovative Ideas In Education, 12(2), 857-868.
MLA Style
B, Amalkrishna K, et al. "SURVEY ON RETAIL INSIGHT GENERATOR: VISION AI FOR CUSTOMER ANALYTICS AND HEATMAPS." International Journal of Advance Research and Innovative Ideas In Education, vol. 12, no. 2, 2026, pp. 857-868.
IEEE Style
Amalkrishna K B, Hariprasad PS, Edwin Davis P, and Ahmed Razal, "SURVEY ON RETAIL INSIGHT GENERATOR: VISION AI FOR CUSTOMER ANALYTICS AND HEATMAPS," International Journal of Advance Research and Innovative Ideas In Education, vol. 12, no. 2, pp. 857-868, 2026.
Vancouver Style
B Amalkrishna K, PS Hariprasad, P Edwin Davis, Razal Ahmed. SURVEY ON RETAIL INSIGHT GENERATOR: VISION AI FOR CUSTOMER ANALYTICS AND HEATMAPS. International Journal of Advance Research and Innovative Ideas In Education. 2026;12(2):857-868.
Harvard Style
B, Amalkrishna K, PS, Hariprasad, P, Edwin Davis, & Razal, Ahmed (2026) 'SURVEY ON RETAIL INSIGHT GENERATOR: VISION AI FOR CUSTOMER ANALYTICS AND HEATMAPS', International Journal of Advance Research and Innovative Ideas In Education, 12(2), pp. 857-868.
Chicago Style
B, Amalkrishna K, et al. "SURVEY ON RETAIL INSIGHT GENERATOR: VISION AI FOR CUSTOMER ANALYTICS AND HEATMAPS." International Journal of Advance Research and Innovative Ideas In Education 12, no. 2 (2026): 857-868.
Turabian Style
B, Amalkrishna K, et al. "SURVEY ON RETAIL INSIGHT GENERATOR: VISION AI FOR CUSTOMER ANALYTICS AND HEATMAPS." International Journal of Advance Research and Innovative Ideas In Education 12, no. 2 (2026): 857-868.
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