Mitkees, Ibrahim M. M.Badr, Sherif M.ElSeddawy, Ahmed Ibrahim Bahgat2019-11-302019-11-302017Cited References in Web of Science Core Collection: 7978-1-5386-4266-5https://ieeexplore.ieee.org/document/8289798Accession Number: WOS:000426982100046A big problem that encounters businesses, especially telecommunications business is 'customer churn'; this occurs when a customer decides to leave a company's landline business for another cable competitor. Therefore, our aim beyond this study to build a model that will predict churn customer through defining the customer's precise behaviors and attributes. We will use data mining techniques such as clustering, classification and association rule. The accuracy and preciseness of the technique used is so essential to the success of any retention attempting. After all, if the company is not aware of a customer who is about to leave their business; no proper action can be taken by that company towards that customer.enOctober University for University for Data MiningCustomer Churnclusteringclassificationassociation ruleCustomer Churn Prediction Model using Data Mining techniquesBook chapter