Big Data Analysis for Consumer Behavior: Evidence from User Segmentation, Recommendation and Opinion Monitoring.

As a matter of fact, digitisation in the 21st century has brought with it an infinitely growing volume of data in recent years. On this basis, the cost of storing data has become less expensive than cleaning it, marking the dawn of the Big Data era. On this occasion, for consumer behavior, big data analytics (BDA) can greatly improve the efficiency of sub-consumer behavior analysis as well as the volume of data, making the research results more accurate. With this in mind, this paper will analyze the applications and implementations of bigdata analysis in the field of consumer behavior. To be specific, this paper is divided into three main parts: first, a brief overview of the background of consumer behavior and BDA; second, a detailed description of the three BDA applications in consumer applied science, and finally, an outlook on the future of BDA in this field. Overall, these results shed light on guiding further exploration of consumer behavior analysis.