Enhancing Customer Experience through Personalized Recommendations: A Machine Learning Approach

Sai Kalyana Pranitha Buddiga, Siddhartha Nuthakki

Abstract: This paper explores how machine learning algorithms can be leveraged to enhance customer experience through personalized recommendations. In today's competitive market landscape, businesses strive to deliver tailored recommendations to their customers to increase engagement, retention, and revenue. By analyzing customer behavior and preferences, machine learning models can predict individualized recommendations for products, services, and content. This paper discusses various machine learning techniques, such as collaborative filtering, content-based filtering, hybrid approaches, and their applications in recommendation systems. Additionally, it examines challenges, best practices, and emerging trends in the field of personalized recommendations, offering insights for businesses seeking to implement effective recommendation systems.

Keywords: Recommender Systems, Machine Learning, Collaborative Filtering, Content-Based Filtering, Customer Experience