Customer churn means the loss of existing customers to a competitor. Accurately predicting customer behavior may help firms to minimize this loss by proactively building a lasting relationship with their customers. In this paper, the application of the factor analysis and the Variable Consistency Dominance-based Rough Set Approach (VC-DRSA) in the customer relationship management (CRM) of the a...

Customer Churn is the term refers to the customers who are in threat to leave the company. Growing number of such customers are becoming critical for the telecommunication sector and the telecom sector are also in a situation to retain them to avoid the revenue loss. Prediction of such behaviour is very essential for the telecom sector and Classifiers proved to be the effective one for the same...

in today’s quality- based competitive world, known as knowledge age, customer attraction is of ultimate importance. in respect to the slogan “customer is always right”, customer relation management is the core of an organizational strategy playing an important role in four aspects of customer identification, customer attraction, customer retaining, and customer satisfaction. commercial organiza...

As deregulation, stew technologies, and new competitors open up the mobile telecommunications industry, churn prediction and management has become of great concern to mobile service providers: A mobile service provider wishing to retain its subscribers needs to be able to predict which of them may be at-risk of changing services and will make those subscribers the focus of customer retention ef...

customers segmentation and analyzing their behavior at fast moving costumer goods (fmgs) industries which deal with a large number of customers with a variety of characteristics causes the marketing activities to be targeted and leads to effective communication with the customers. segmentation, a data mining approach, which leads to the discovery of similar groups of customers, is usually done ...

Customer churn may be a critical issue for banks. The extant literature on statistical and machine learning for customer churn focuses on the problem of correctly predicting that a customer is about to switch bank, while very rarely considers the problem of generating personalized actions to improve the customer retention rate. However, these decisions are at least as critical as the correct id...

Modern companies accumulate a vast amount of customer data that can be used for creating a personalized experience. Analyzing this data is difficult and most business intelligence tools cannot cope with the volume of the data. One example is churn prediction, where the cost of retaining existing customers is less than acquiring new ones. Several data mining and machine learning approaches can b...

Data mining plays important role in marketing and is quite new. Although this field expands rapidly, data mining is still foreign issue for many marketers who trust only their experiences. Data mining techniques cannot substitute the significant role of domain experts and their business knowledge. In the other words, data mining algorithms are powerful but cannot effectively work without the ac...