Machine Learning-Based Customer Behavior Analysis for E-commerce Platforms

Abstract

Providing a method that is founded on machine learning to analyze the behavior of customers on e-commerce platforms is the objective of this research study, which aims to provide a method. It is necessary for companies that engage in e-commerce to know and anticipate the behavior of their customers to enhance the success of their marketing efforts and to improve the amount of enjoyment that they deliver to their customers. This is because the popularity of buying online is expanding at a rate that is accelerating at an exponential rate. To identify patterns and trends in consumer behavior, our solution makes use of machine learning techniques to analyze large-scale transactional data, user interactions, and demographic information. This analysis is made to detect patterns and trends. Within the context of consumer behavior, this analysis is carried out to identify patterns and trends. Through the utilization of techniques such as clustering, classification, and predictive modeling, we can recognize distinct client types, estimate purchase trends, and anticipate future behaviors.