Data mining of an ATM machine in ۲۴ hours exploiting clustering and forecasting models for marketing strategies: A case study in one of the branches of Bank Melli Iran

Data science, stem from statistical science, has emerged to make the best use of extant data. It is known as one of the popular branches in the industrial engineering. In view the fact that a large number of data have generated in the various businesses, data science can substantially assist the managers to find specific patterns for prediction. In this regard, this paper applies the k-means approach to achieve the optimal cluster for the considered data. Likewise, the neural network algorithm is employed to forecast the future result. Using a regression model, the important factors for transaction success is also determined, Ultimately, the best marketing strategies have suggested. Eventually, a case study in one of the branches of Bank Melli Iran is conducted, through which important managerial insights are extracted.

Keywords:

Data mining , Marketing strategies , Bank data , Clustering , forecasting