Abstract

Research on consumer behavior has become essential in recent years as it plays an important role in business marketing and growth. Consumers are the king of the market. For-profit organizations cannot function without customers. All the activities of the company end with the consumer and their satisfaction. Consumer behavior is the study of consumers and how they choose or eliminate products. This theory extends not only to products but also to services consumed. To develop a framework for studying consumer behavior, first look at the factors that influence consumer buying behavior, as well as the various thinking paradigms that have influenced the progress and discipline of consumer research. Modeling customer behavior is nothing more than creating a mathematical structure to map the general behavior of a particular customer group. This is done to predict how consumers will react in a particular situation. The purpose of the survey is to better understand consumer behavior by examining the factors that influence the consumer's purchasing process. The main purpose of studying consumer behavior is to understand how consumers feel and think. Building a recommendation engine is another application for studying consumer behavior. The recommendation engine basically recommends several products based on a variety of factors, including previous purchases by consumers, age, etc. It's a kind of data filtering tool that uses machine learning algorithms to recommend the most relevant items to a particular customer. The purpose of this paper is to analyze consumer segmentation and sentiment regarding product reviews and build a product recommendation system.

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