Predicting The Lifetime Value of Sports Customers Based on Neural Network Group Technique (GMDH)

The present research is practical due to providing a new method for predicting customer lifetime value and application in increasing the profitability of sports organizations, and in terms of the method of data collection, it is field type. In this research, using the GMDH artificial neural network, the lifetime value of customers in sports clubs has been calculated and predicted. The sample size in the qualitative section was identified using a targeted non-random method, 18 experts (university professors and sports managers) who had expertise in the fields related to the subject, and direct interviews were conducted with them or an open-ended questionnaire was used. After that, the factors were analyzed and the research tool was made. The overall reliability of the questionnaire was calculated as 0.85. In the quantitative part, the statistical population includes 413 male and female athletes who have at least 6 months of sports activity and membership in one of the sports clubs located in the western and northwestern provinces of the country . They had, it was distributed; that due to the dispersion and wideness of the target society, the cluster sampling method was used. The results showed that using this method it is possible to predict the value of life span with an accuracy of more than 95%. Also, the existence of sports infrastructure, financial support of clubs, general well-being of society, effectiveness of sports services, smart sports management and the skill of the coach have a high impact on increasing the customer's lifetime value.