Introduction

The telecom sector is witnessing a massive increase in data, and by analyzing this massive data, telecom operators can manage and retain customers. It is also important for companies to be able to predict the amount of income they may receive from their active customers. For this purpose, they need models able to determine customer loyalty. The cost associated with customer gain is usually higher than the cost associated with maintaining it. Prediction can be directed at customer loyalty to identify both customers who have great loyalty to their preservation as well as customers with intentions to change to the competitors. This capability is necessary, especially for modern telecommunications operators. Nowadays companies face more complexity and competition in their business and need to develop innovative activities to capture and improve customer satisfaction and retention. Growing profitability is the goal of most companies, to reach this goal, companies must provide an analysis of customer relationship management (CRM) and provide appropriate marketing strategies. Some studies provided a new model of transactions based on both the services and customer satisfaction and showed that the price is not the only measure affecting customer buying decisions, but it is also important that both the customer and the company agree on product value and good customer services. Therefore, organizations should not seek to develop a product to satisfy their customers, but they must follow the customer purchasing behavior and offer distinct products for each segment. In other words, segmenting customers based on purchasing behavior is necessary to develop successful marketing strategies, which in turn cause the creation and maintenance of competitive advantage. Current methods of customer value analysis which are based on past customer behavior patterns or demographic variables are limited to predict future customer behavior. So, better patterns were exch