Research On Segmentation Of Spring Festival Return Customers Based On Data Mining

As the intensification of the mobile communication market competition and the diversification of customer requirements for products and services, the concept of customer segmentation influences deeply all telecom operators. Today, telecommunication market has been divided into three parts, the operators must supply the best service for the customer to become the finale winner. Customer segmentation is the most important part in mobile communication market, it is the foundation of supplying to the customers with products and services. Through customer segmentation, we can accurately understand the needs of customers and customer consumption behavior characteristics, and make correct marketing strategy, looking for the right market positioning for our products.This thesis uses the kunming mobile company’s Spring Festival return customers as the research object, and based on the analysis of the characteristics of mobile business and user behavior, choose the different segmentation dimensionality and Variable indicators, establish customer segmentation model We select6000samples data source as the data analysis from the Business Operation Support System, then do data preprocessing to data sources, such as missing value, abnormal values, standardization of data processing, etc.Then this thesis uses K-means and Apriori algorithm of data mining for customer clustering and association rules analysis respectively. Clustering and analyzing the source data by statistical analysis software SPSS, and using discriminant analysis method to verify the clustering results, then obtaining the optimal clustering results. Through the analysis of association rules, some consumer behavior rules of value-added service are founded.Finally, this thesis puts forward some marketing strategy suggestions for the company according to the data mining results. We studied the whole process on customer segmentation of kunming mobile company’s Spring Festival return customers, builded the customer segmentation model analyzed the regularity of value-added service consumption behavior. The customer segmentation results are certain rationality and practicability, it influenced certainly in formulating pricing package and other related marketing decisions.