Recently, telecommunication companies have been paying more attention toward the problem of identification of customer churn behavior. In business, it is well known for service providers that attracting new customers is much more expensive than retaining existing ones. Therefore, adopting accurate models that are able to predict customer churn can effectively help in customer retention campaign...

customers are the most valuable asset of an organization. due to high contest in the business field, it is necessary to regard the customer relationship management (crm) of the enterprise. data mining and machine learning methods been utilized by businesses in recent years in order to improve crm. crm is the strategy for building, managing, and strengthening loyal and long lasting customer rela...

Customer churn is the term which indicates the customer who is in the stage to leave the company. Particularly it is happening recurrently in the telecommunication industry and the telecom industries are also in a position to retain their customer to avoid the revenue loss. Prediction of such behaviour is very vital for the present market and competition and Data mining is the one of the effect...

Customer churn has become a major problem within a customer centred banking industry and banks have always tried to track customer interaction with the company, in order to detect early warning signs in customer's behaviour such as reduced transactions, account status dormancy and take steps to prevent churn. This paper presents a data mining model that can be used to predict which customers ar...

The present study attempts to establish a new framework to speculate customer lifetime value by a stochastic approach. In this research the customer lifetime value is considered as combination of customer’s present and future value. At first step of our desired model, it is essential to define customer groups based on their behavior similarities, and in second step a mechanism to count current ...

in today's competitiveenvironment, customers are the most important asset to any company. therefore,in order to retain customers, it is essential to understandtheirbehaviour for developing effective strategies. one of the most commonmethods for customer analysis is market segmentation that helps companies todevelop marketing technique by dividing market into several smaller homogeneousgrou...

The Customers are the base of many successful businesses; thus, all sectors starting to understand how important it is gain client satisfaction. technical infrastructure has expanded quickly, changing businesses operate. Due growing business competition, importance marketing techniques, and customers' increasingly aware behaviour in recent years, leaving organization a crucial issue one most wo...

Churn prediction is an important factor to consider for Customer Relationship Management (CRM). In this study, statistical and data mining techniques were used for churn prediction. We use linear (logistic regression) and non-linear techniques of Random Forest and Deep Learning architectures including Deep Neural Network, Deep Belief Networks and Recurrent Neural Networks for prediction. This i...

Purpose – Churn prediction is a very important task for successful customer relationship management. In general, churn prediction can be achieved by many data mining techniques. However, during data mining, dimensionality reduction (or feature selection) and data reduction are the two important data preprocessing steps. In particular, the aims of feature selection and data reduction are to filt...

Marketing literature states that it is more costly to engage a new customer than to retain an existing loyal customer. Churn prediction models are developed by academics and practitioners to effectively manage and control customer churn in order to retain existing customers. As churn management is an important activity for companies to retain loyal customers, the ability to correctly predict cu...