Telecom customer segmentation and precise package design by using data mining

Abstract

Changes in the form of communication have prompted the telecommunications industry to flourish. In the "big data era" of information explosion, as one of the leading industries in the information age, the development of the telecommunications industry depends not only on communication technology, but also on the ability of enterprises to optimize resource allocation. At present, the information resources owned by telecom companies mainly come from customers. During the development process, they have accumulated a large amount of customer data, which truly and objectively reflects the behavior of consumers. This paper is dedicated to combining data mining technology with the rich data resources of the telecom industry and the latest marketing theories, not only effectively helping subdivide the telecommunications customer market, but also supporting telecommunications companies in developing more accurate and efficient marketing strategies. In addition, data analysis method such as factor analysis, regression analysis and discriminant analysis are used to analyze the demographic, business, SMS messages and expense characteristics of telecom customers, providing a new vision and reference for the telecom industry to achieve accurate packaging design. Based on the above research results, a discriminant model for the loss of telecom customers is constructed, which will help telecommunications companies to obtain a control method for telecom customer management risk. At last, data mining technology is used to optimize the combination design of telecommunication services, which offer effective advice on precise telecom package design to telecommunications companies.