How AI Contributes to Tailored Online Product Suggestions

Abstract

In order to provide a more customised online shopping experience, artificial intelligence (AI) is vital in suggesting products to specific individuals. By delving into the most important methods and algorithms used to evaluate user data and preferences, this study investigates the role of AI in the development of tailored product suggestions. We go over how AI-powered recommendation systems may help e-commerce sites boost engagement, conversion rates, and revenue. We also discuss the many recommendation algorithms and their pros and cons in producing relevant and accurate product choices, including collaborative filtering, content-based filtering, and hybrid methods. We also analyse user interactions, comments, and purchase history to determine how machine learning models might improve suggestion accuracy over time. With the help of AI, online stores can personalise product recommendations based on each customer's tastes and requirements, which improves the shopping experience and increases loyalty. By shedding light on the inner workings and potential advantages of AI-driven product suggestions in e-commerce, this study hopes to encourage more investigation and development in this dynamic area.