Application of mining algorithm in personalized Internet marketing strategy in massive data environment

Abstract

Internet marketing requires a personalized marketing strategy. In this study, the application of data mining in personalized Internet marketing was studied. Based on the mining algorithm, a personalized marketing method was designed. Through the calculation of frequent closed item sets and support counts of positive and negative samples, the interval with a high success rate for marketing was obtained. With performance analysis, it was found that the success rate of the marketing method proposed in this study improved 8% compared with the traditional marketing method and had a better performance under the smaller interval number and smaller minimum success number. After applying the designed method in telecommunication enterprise A, it was found that after adopting the marketing method of this study, the marketing success rate of enterprise A increased from 2.72 to 6.31%, which indicated the effectiveness of the method. The research results of this study verify the role of data mining algorithms in Internet marketing, which is conducive to the further application of mining algorithms in personalized marketing and innovation of business modes.