Title :
An Empirical Study of Customer Churn in E-Commerce Based on Data Mining
Author :
Wu Heng-liang ; Zhang Wei-wei ; Zhang Yuan-yuan
Author_Institution :
Sch. of Manage. Sci. & Eng., Shandong Inst. of Bus. & Technol., Yantai, China
Abstract :
With the e-commerce market competition becoming more and more furious, it has become one of the focuses of companies that how to avoid customer churn and carry out customer retention. This paper applies many techniques of data mining to the research of customer churn, such as clustering analysis, decision tree, neural network, etc, establishes an e-commerce customer churn model and analyzes the factors which influence customer retention.
Keywords :
consumer behaviour; customer relationship management; data mining; decision trees; electronic commerce; neural nets; pattern clustering; clustering analysis; customer churn; customer retention; data mining; decision tree; e-commerce market competition; neural network; Analytical models; Artificial neural networks; Companies; Data mining; Data models; Decision trees;
Conference_Titel :
Management and Service Science (MASS), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5325-2
Electronic_ISBN :
978-1-4244-5326-9
DOI :
10.1109/ICMSS.2010.5576627
