TY - JOUR ID - 1187 TI - Analyzing Customers of South Khorasan Telecommunication Company with Expansion of RFM to LRFM Model JO - Journal of AI and Data Mining JA - JADM LA - en SN - 2322-5211 AU - Babaiyan, V. AU - Sarfarazi, Seyyede A. AD - Department Of Computer Engineering, Birjand University of Technology, Birjand, Iran. Y1 - 2019 PY - 2019 VL - 7 IS - 2 SP - 331 EP - 340 KW - LRFM Model KW - TwoStep algorithm KW - k_Means algorithm DO - 10.22044/jadm.2018.6035.1715 N2 - 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. UR - https://jad.shahroodut.ac.ir/article_1187.html L1 - https://jad.shahroodut.ac.ir/article_1187_2c51c149ee9fdd0b4dc816a5ba235c0f.pdf ER -