AI-Powered Visual E-Commerce

The explosion of social media and artificial intelligence (AI) has turned online shopping more interactive and
engaging. This research introduces AI-based Visual E-Commerce, a novel platform that combines short-form video content
(reels) with AI-based personalized product recommendations. Drawing inspiration from Instagram and Flipkart, this system
facilitates users to browse clothing items through dynamic reels, using computer vision and machine-learning algorithms to
interpret user preferences and make suitable apparel recommendations. The design increases user engagement by offering an
immersive, scroll-driven shopping experience where customers can effortlessly switch from watching reels to buying products.
The recommendation engine employs deep learning concepts to forecast user interests by analyzing watching patterns,
interaction behavior, and purchasing history. Besides, the platform integrates natural language processing (NLP) and sentiment
analysis to enhance product recommendations and enhance customer satisfaction. The outcome of prototype deployment reveals
higher user interaction and conversion rates than standard image-based e-commerce sites. This research presents the
capabilities of AI-based visual commerce to revolutionize digital retail with an intelligent and engaging shopping experience.
Keywords: AI-based e-commerce, reel-based shopping, personalized recommendations, deep learning, computer vision, user
engagement, Natural Language Processing(NLP)