Discriminant analysis text to predict customer loss in the real estate industry
DOI: 10.23977/acccm.2020.020106 | Downloads: 5 | Views: 723
Yu Zhao 1, Tong Bai 2, Yingnan Jia 3
1 Institute of Date Science, City University of Macao, Avenida Padre Tomás Pereira, Macao, China
2 Institute of Business Adminstration, Krirk University, Ram Inthra Rd, Bangkok, Tailand
3 School of Economic and Management, SHIHEZI University, Shibeisi Rd, Xinjiang, China
Corresponding AuthorYu Zhao
Customer churn in a broad sense means that customer service is terminated because the behavior of the customer or real estate operator is contrary to the service agreement. In fact, in real life, the main reason for the loss of customers is because customers are not satisfied with the real estate operator's service attitude and manner, or other real estate operators give more favorable prices. Customer churn forecasting is the process of using historical data recorded by customers to identify potential churning customers. He is a very important concern for the various service industries. Especially in the highly competitive financial, telecommunications, real estate, and other industries.
KEYWORDSLinear Discriminant Analysis, Customer Loss, Real Estate Industry
CITE THIS PAPER
Yu Zhao, Tong Bai, and Yingnan Jia, Discriminant analysis text to predict customer loss in the real estate industry. Accounting and Corporate Management (2020) 2: 67-70. DOI: http://dx.doi.org/10.23977/acccm.2020.020106.
 WEICP, TANGCI.Turning telecommunications call details tochurn prediction: a data mining approach[ J] . Expert Systems with Applications, 2002, 23( 2) : 103- 112.
 LOUIS A C. Data mining and causal modeling of customer[J] . Telecomm unication Systems, 2002, 21( 2) : 381- 394.
 ROSSET S, EINAT N. Integrating customer value considerations intopredictive modeling[ C] / /Proc of the 3rd IEEE International Conference on Data Mining. Washington DC: IEEE Computer Society,2003: 283- 290.
 CARDELLN S, GOLOVNYA M, STEINBERG D. Churn modeling for mobile telecommunications[ EB /OL] . ( 2003-06) . http: / / www.salford-systems. com/ doc / churnwinF08. pdf.
 QI Jia-yin, ZHANG Yang-ming, ZHANG Ying-ying, et al. TreeLogitmodel for customer churn prediction[ C] / /Proc of Asia-Pacific Conference on Services Computing. Washington DC: IEEE Computer Society, 2006: 70- 75.
 LUO Bin, SHAO Pei-ji, LIU Juan. Customer churn prediction basedon the decision tree in personal handyphone system service[ C] / /Procof International Conference on Service Systems and Service Management. 2007: 1- 5.
 KIM H S, YOON C H. Determinants of subscriber churn and customer loyalty in the Korean mobile telephony market[ J] . Telecommunications Policy, 2004, 28( 9) : 751- 765.