Analysis of implementation for big data techniques in consumer behavior

Abstract

Consumer behavior can refer to both the purchasing behavior of consumers towards goods and the decision-making behavior of consumers when choosing goods, the research in this field involves psychology, marketing, and other disciplines. As a popular data mining and processing technology, big data technology has powerful information analysis capabilities. Therefore, with this in mind, applying big data technology to consumer behavior research can greatly improve the efficiency. This study focuses on the implementation for big data techniques in consumer behavior, including application scenarios, application methods, as well as application efficiency. The AIDMA, AISAS, and SOR models are suitable for using big data analysis technology. Big data technology helps enterprises influence external factors in consumer behavior factors, thereby influencing consumer decision-making behavior through internal perception factors. Overall, these results aim to collect and summarize relevant knowledge about consumer behavior and big data for future scholars to investigate and explore the implementation schemes.