E-COMMERCE WEBSITE WITH AI-BASED PRODUCT RECOMMENDATIONS

ABSTRACT The rapid expansion of digital commerce has transformed the way individuals purchase goods and services. Traditional e-commerce websites provide customers with access to thousands of products; however, the abundance of choices often creates difficulty in locating relevant items. To address this challenge, modern e-commerce platforms increasingly integrate Artificial Intelligence (AI) to deliver personalized product recommendations. This project focuses on the design and implementation of an E-Commerce Website with AI-Based Product Recommendations. The system was developed to analyze user interactions, browsing patterns, and purchasing behavior in order to recommend products that align with customer preferences. The recommendation engine utilizes machine learning techniques to improve product discovery and enhance user engagement. The research adopted a system development methodology involving requirement analysis, system design, implementation, and evaluation. A prototype web application was developed incorporating essential e-commerce functionalities such as product browsing, account management, shopping cart, order processing, and intelligent recommendation features. The results indicate that integrating AI-driven recommendation systems significantly improves customer satisfaction and purchase likelihood. The project demonstrates that AI-powered recommendation engines can enhance the efficiency and profitability of online retail platforms. Ultimately, this research highlights the importance of personalization in digital commerce and shows how artificial intelligence can reshape the online shopping experience.