Abstract
Under fierce market competition, there is a need for enterprises to analyze and predict the behavior of consumers in order to improve the market competitiveness. We find that in the previous literature, there is little specific systematic summary and research on the methods to predict customer behavior. Thus, in this paper, we discuss relevant concepts of customer behavior and predict consumer behavior by studying the operation mechanism of Big Data Analysis (BDA), Decision Tree (DT) and Consumer Relationship Management (CRM). We also study the application of each technology to enterprises in different fields and its impact on consumer behavior. BDA can efficiently organize a large amount of data into several variables that is related to the prediction and provide a reference prediction for the business. DT can effectively improve the accuracy of market segmentation, classify customers into sub-customer groups with distinct consumption characteristics, and help enterprises make targeted decisions. CRM can collect customer information through data sampling to build a comprehensive view of customers, and create customer analysis and prediction models according to the different needs of the enterprise. Studying the past consumer behavior can help enterprises to better develop products and make personalized decision plans for specific customer groups.
Published Version
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