Construction of Precision Sales Model for Luxury Market Based on Machine Learning

Abstract

With the rapid development of Internet information technology, the amount of various types of data has surged, and people have entered the era of Big Data. With the changes in the market environment, media environment and consumer behaviors, the marketing method in the mobile Internet era is bound to be an integrated, interactive, and precise marketing method that connects online and offline. In the context of this era, luxury brand marketing improves brand competitiveness by combining new marketing methods. The method used in this paper is machine learning. Many studies have shown that the larger the sample size processed by machine learning, the more accurate the effect of machine learning. Therefore, machine learning will become the core force in Big Data technology. Among them, this paper adopts the decision tree model, which first classifies the data, then uses the induction principle to generate readable decision tree rules and finally analyses and judges the decision data. According to the test results, the arithmetic mean calculation method is used to calculate the operational efficiency of the data flow balance height. The algorithm proposed in this paper is 20% more effective than the traditional algorithm.