The Design And Implementation Of Telecom Customer Retention Based On Data Mining Technology

Data mining is the currently hot topic of artificial intelligence and database research in the field, highly automated analysis of corporate data, make inductive reasoning, dig out potential models to help decision-makers to adjust marketing strategies, reduce risk, make the right decisions.Communications industry in China has experienced a number of split reorganization, breaking the monopoly, forming a three competitive landscape. In the increasingly intense competition in the mobile communications market environment, the telecom operators are actively in the process of market share, while doing everything to develop new markets, on the other hand attaches great importance to the stability of the stock market, the data mining technology in customer relations management, care depth of existing customers, and to maintain and enhance the value of activities.Based on the current development of China’s telecommunications industry market, customers maintain the status quo and data mining techniques are used in various fields of customer relationship management, for the province of telecom operators to maintain the status quo customer research and analysis conducted for enterprises based on operational experience, choose single warning condition has lost a tendency for clients to send a single warning maintain, accuracy and efficiency is not ideal, which combined with the actual job requirements, this paper based on data mining technology, customer retention system design, and a provincial telecom operators part of the user data, for example, design and construction measures customer churn prediction model of customer retention is analyzed.In this paper, a provincial telecom operators customer retention systems analysis and design, providing a standardized and systematic management platform, to facilitate management more convenient, efficient and accurate manner for customer data collection and analysis, and by the loss of early-warning model of customer off-grid more accurate risk assessment needs to focus on maintaining the lock target customer groups, marketing resources to achieve rational use and enhance customer loyalty for companies to create significant economic benefits, with a strong practical application and popularization.