Consumer Behavior Analysis

Ghanasiyaa Sundareswaran, Harshini Kamaraj, S. Sanjay, Akalya Devi, Poojashree Elangovan, Kruthikkha P
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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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消费者行为分析
近年来,对消费者行为的研究变得至关重要,因为它在企业营销和发展中起着重要作用。消费者是市场之王。盈利性组织没有客户就无法运作。公司的一切活动都以消费者和他们的满意为结束。消费者行为是对消费者以及他们如何选择或淘汰产品的研究。这一理论不仅适用于产品,也适用于消费的服务。要建立一个研究消费者行为的框架,首先要看看影响消费者购买行为的因素,以及影响消费者研究进展和学科的各种思维范式。客户行为建模只不过是创建一个数学结构来映射特定客户群体的一般行为。这样做是为了预测消费者在特定情况下的反应。调查的目的是通过检查影响消费者购买过程的因素来更好地了解消费者行为。研究消费者行为的主要目的是了解消费者的感受和想法。构建推荐引擎是研究消费者行为的另一个应用。推荐引擎基本上根据各种因素推荐几种产品,包括消费者以前的购买行为、年龄等。这是一种数据过滤工具,使用机器学习算法向特定客户推荐最相关的商品。本文的目的是分析消费者对产品评论的细分和情感,并建立一个产品推荐系统。
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