Analysis of Communication Enterprises' Customers Segmentation Based on Data Mining

Abstract:

Application of data mining in mobile communication enterprises can help the enterprises conduct customers subdivision, understand characteristics of consumer behavior and develop appropriate product service systems based on different subdivided groups to occupy more market shares and provide better services for customers. By applying cluster analysis method in data mining and using k-means algorithm, this paper analyzes the collected mobile service consumption data with college students as samples, concludes behavioral characteristics of the mobile service consumption of three type college students and makes proposals from the perspective of operators.

• Periodical: Applied Mechanics and Materials (Volumes 543-547)
• Pages: 4464-4467
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.543-547.4464
• Online since: March 2014
• Authors: Jing Zhao*, Nan Wei, Hui Li, Yue Ling Liu
• Keywords: Cluster Analysis, Customer Segmentation, K-Means Algorithm, Mobile Billing Data

References

[1] Liu Hui. Research on Telecom Market Segmentation and Call Features Based on Data Mining – Taking Sichuan Telecom Market as an Example [D]. Chengdu: Master Thesis of Southwestern University of Finance and Economics, (2008).

[2] Gong Chun, Wang Zhenglin. MATLAB Language Commonly Used Algorithm Collection[M]. Beijing: Electronic Industry Press. (2008).

[3] Zhang Defeng , Zhou Yan , Lei Xiaoping. Detailed Discussion on Application of MATLAB in Statistics and Engineering Data Analysis[M]. Beijing: Electronic Industry Press. (2010).

[4] Zi Yawei. Research on Mobile Customer Segmentation Based on Consumer Behavior [D]. Beijing: Master Thesis of Beijing University of Posts and Telecommunications. (2006).

[5] Niu Kun. Research on Several Key Technologies of Cluster Analysis and Their Application in Telecom Field [D]. Beijing: PHD Thesis of Beijing University of Posts and Telecommunications. (2007).