Research Of Analytical Model Of Railway Freight Customer Churn Based On Business Intelligence

Customer churn is a common problem that the enterprises facing, and customer churn management is also an important part of customer relationship management (CRM). Although there are a lot of researches on customer churn by data mining technology now, which were focus on the telecommunications, finance, etc.. As the freight competition is increasing gradually, the phenomenon of customer churn become more and more intensified. It’s becoming an urgent problem need to be solved that how to find customer churn tendency in time and minimizing losses with minimum resources. Around intelligence technology, a study is carried out on railway freight customer churn warning.Based on the understanding of data warehouse, OLAP and data mining, and current railway freight customer relationship management situation, it raised the customer churn analysis system for railway freight, which divided the customer churn management into three stages, and the customer churn management scheme were studied based on the system. It raised the data warehouse model, KGFM customer segmentation models, and identification of customer status with customer synthetic value, and build a customer churn warning analysis scheme by using decision-tree method. The scheme was implemented with sample data by using database and data mining tools. The customer churn warning model were evaluated, which proved that the predict outcomes is closed to actuality. It discussed the model application and the strategy of customer relationship management.The customer churn management system and research program here can offer some references for our railway freight customer churn management.