AI-DRIVEN PERSONALIZATION IN E-COMMERCE PLATFORMS

Abstract

Personalization in e-commerce platforms enhances customer experience by tailoring product recommendations, marketing strategies, and user interfaces based on individual preferences and behavior. This paper explores the role of Artificial Intelligence (AI) in driving personalization, focusing on machine learning algorithms, natural language processing, and deep learning techniques. We analyze various personalization strategies, including collaborative filtering, content-based filtering, and hybrid approaches. Additionally, the paper discusses challenges such as data privacy, scalability, and algorithmic bias. Case studies from Pakistani e-commerce companies highlight practical applications and benefits. The study concludes with future research directions to optimize AI-driven personalization in emerging markets.