Analyzing Customers of South Khorasan Telecommunication Company with Expansion of RFM to LRFM Model | ||
| Journal of AI and Data Mining | ||
| مقاله 11، دوره 7، شماره 2، تیر 2019، صفحه 331-340 اصل مقاله (1.46 M) | ||
| نوع مقاله: Original/Review Paper | ||
| شناسه دیجیتال (DOI): 10.22044/jadm.2018.6035.1715 | ||
| نویسندگان | ||
| V. Babaiyan؛ Seyyede A. Sarfarazi | ||
| Department Of Computer Engineering, Birjand University of Technology, Birjand, Iran. | ||
| چکیده | ||
| Telecommunication Companies use data mining techniques to maintain good relationships with their existing customers and attract new customers and identifying profitable/unprofitable customers. Clustering leads to better understanding of customer and its results can be used to definition and decision-making for promotional schemes. In this study, we used the 999-customer purchase records in South Khorasan Telecommunication Company which has been collected during a year. The purpose of this study is to classify customers into several clusters. Since the clusters and the number of their members are determined, high-consumption users will be logged out of the system and high-value customers who are missed will be identified. In this research we divided our customers into five categories: loyal, potential, new, missed and high-consumption by using the Clementine software, developing the RFM model to the LRFM model and TwoStep and k_Means algorithms. Thus, this category will be a good benchmark for company's future decisions and we can make better decisions for each group of customers in the future. | ||
| کلیدواژهها | ||
| LRFM Model؛ TwoStep algorithm؛ k_Means algorithm | ||
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