CRM Application using fuzzy clustering algorithm

Customer Relationship Management (CRM) is the process of managing a good relationship with customer and retain customers .The telecom industry provides the services to the customer in order to satisfy their needs and requirements. It handles the large data of customers. but due to market dynamicity and competition, company face one problem that is loss of valuable customers. To overcome this, we need to understand the behavior of customers in terms of usage level of provided services. Data mining is the efficiently used tool in CRM.it collects all the information about the customers. Also extract the patterns from the data to transform into knowledge information. Clustering is one of the data mining techniques used in customer segmentation. This segmentation approach is achieve using fuzzy logic. With the help of this it forms the fuzzy cluster. This cluster represents the group of customers regarding particular services. This technique is referred to as soft clustering also called as fuzzy clustering. In Soft clustering each data point has a probability of being in each cluster. The data points are assigned memberships value for each of the clusters. The complete operation is known as Fuzzy C-means (FCM) Clustering algorithm. It also handles the extreme outliers by assigning them a very small membership degree in surrounding clusters. The formation of clustered data represents the output. This paper focuses on applying FCM algorithm to calculate the churn ratio of a particular service accurately.