Research On University Student 's Customer Identification Model Based On Data Mining

With the high-speed development of mobile Internet, telecommunication business steadily, user data continue to accumulate, the big data era, the pattern of the whole communication industry competition is more and more fierce.Customer data has become an important resource for the accumulation of resources around the industry-oriented marketing strategy.The telecommunications industry as the core user base carrier communication data, as 4G (fourth generation mobile communication technology) growing popularity, the user as a core element of profit growth has become a major focus of contention communications carriers.As the main force in the customer base, the young user communication activity rising, the market share of the telecommunications operators play a crucial role. And college students on behalf of clients as young users, this part of the crowd behavioral analysis has important significance.In this paper, the basic information about the campus area customer base K and municipalities of China Mobile as the basis, in accordance with standard commercial understanding CRISP-DM process model, data understanding, data preparation, model building, model evaluation, model deployment of a total of six stages of the content data excavation work, the choice of data mining tools SPSS Clementine12.0.3, C5.0 decision tree algorithm, neural network algorithm, two logistic regression algorithm model for college students to establish customer identification and assessment, to choose the best model, and validate the uniqueness of the model and then the model deployment.On the basis of this model, the business personnel according to the communication situation of the university students’customer to develop effective marketing strategies, to better serve customers for college students.