With the advent of AI, every business sector is harnessing AI’s potential to improve customer satisfaction and optimize their business processes. Retail business has become highly competitive due to the competition from eCommerce platforms as well as the new players in brick and mortar. All the players are trying to maximize their market share through various avenues. Commoditization has increased which means the margins are now lower than ever before. It is imperative to study every type of customer interaction data. That helps in building an understanding of changes in customer preferences ahead so that retailers can predict trends in buying behavior. This will eventually help in moving volumes. Although the retail stores are capturing a lot of customer interaction data each day, it is not being utilized up to its potential for drawing any meaningful insights. One of the ways to do that is by leveraging the customers’ activity captured by the store’s cameras. To derive real-time customer behavioral insights, we developed a Computer Vision and AI-powered solution that consumes the video feeds captured by cameras in the stores and provides useful notes on customer-product interactions The following white paper elaborates our solution that is implemented using advanced technologies like Convolutional Neural Networks, Image Processing, Object Detection, and Tracking Algorithms. It enriches the retailers’ understanding of customers’ behavior by providing analytics on purchase patterns, product placements, service times, etc.