Construction of e-commerce platform precision marketing classification model based on big data algorithm

Abstract

Big data technology is the new development of information technology, which can realize the rapid integration of information. Compared with the traditional information integration technology, it is more convenient and faster, and is widely used in all walks of life to obtain product and customer information. In the era of big data, precision marketing is based on data, multi-dimensional analysis of enterprise users' behavior and attribute data, and targeted marketing activities. In this paper, the classification model of e-commerce platform precision marketing based on big data algorithm is constructed. Taking common big data classification algorithms as the theoretical basis of the experiment, this paper introduces the historical behavior data of e-commerce websites as training data, and compares the training results of each algorithm, so as to find and analyze problems and draw conclusions. The experiment uses Python language to realize the data algorithm. The results show that the improved Apriori algorithm can effectively improve the computational efficiency of the algorithm, at the same time improve the bias of Apriori algorithm, and improve the accuracy of the algorithm. Big data classification algorithm can be effectively used in precision marketing to solve classification problems, and the model has high accuracy, which can be used in actual precision marketing.