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Acquiring and retaining profitable customers are major concerns of a business. In this paper, the customers of the Restoration and Beauty Clinic of Iran University are segmented using three value types: current value, expected value, and loyalty in a case study to predict the probability of customer churn and future purchase services in the clinic.

This study utilized customers' data records with nine data fields (socio‐demographic and transactional) from three year's transactions of the clinic. Logistic regression as a data mining technique is then used to predict the future behavior of the customers. In addition, the verification and the validation of the models are done using lift charts.

This research segments the customers of the clinic into four categories based on three values (current value, expected value, and loyalty). Then simple marketing strategies that might be adopted are suggested. These strategies might help the shareholders and experts of the clinic to promote relationships with patients and deliver better services to attract and retain their customers.

The results of this research enable public health agencies to evaluate the effectiveness of their policies and detect their shortcomings in order to better serve patients. Also, it will help to increase their profits from the clinics and raise customer satisfaction.