Railway Passenger Customer Relationship Management Research Based On Data Mining

With the rapid development of modernization, the vicarism among various modes oftransportation is obvious, passengers have become the most important resource to compete ofthe various modes of transport, good customer relationship is a pillar to enhance their owndevelopment and competition, the same, railway passenger customer relationshipmanagement is the bridges to attract visitors, cultivate loyal tourists and build emotionalconsumption between passengers and the railway.The information development of the railway and the real name ticketing makespassenger system accumulated a large amount of data, how to extract useful informationhidden in these data, found the characteristics and laws of the passenger, has become aresearch focus of many scholars, this paper uses data mining technology to model and analyzepassenger data.Firstly, this paper by comparing the domestic and international railway passengertransportation development present situation, found the relationship management customer ofChina Railway is at the start stage, management and application of passenger data informationis not perfect, then makes a deep research on customer relationship management of China’srailway passenger transport system. The research process can be divided into the followingparts:(1) Establishing the system structure of customer relationship management of China’srailway passenger transport, and detailedly designing of the function modules of each part.Gives the flow chart of the data mining application in RPCRM, and discusses the mainaspects of data mining are applied in RPCRM.(2) using the decision tree classification method to classify the passengers, using J48algorithm to model the passenger data, based on the analysis of the model prediction, foundthe characteristics of different categories of visitors and which the main client for passengertransport department, gives the reference of reasonable marketing strategies for passengerwork.(3) by using K-Means clustering to analyze passenger satisfaction, found the veryimportant factors, the general important factors and important factors which are visitorsthought, and which factors of passenger’s satisfaction are lower, directs improvement anddevelopment of passenger service.