Consumer Behavior Analytics using Machine Learning Algorithms

Abstract

User-generated content in the form of reviews, ratings, and comments can be analyzed for greater insights for enterprise use. The analysis of such consumer behavior is helpful to understand the consumer's requirements and predict their future intentions towards the service. Through this cognitive study, E-commerce Organizations can track the usage and sentiments attached to their products and take appropriate marketing approaches to provide a personalized shopping experience for their consumers, thereby increasing their organizational profit. This paper aims to employ data-driven marketing tools, such as data visualization, natural language processing, and machine learning models that help in understanding the demographics of an organization. We also build recommender systems through collaborative filtering, neural networks, and sentiment analysis.