Analyzing Customers of South Khorasan Telecommunication Company with Expansion of RFM to LRFM Model
محل انتشار: مجله هوش مصنوعی و داده کاوی، دوره: 7، شماره: 2
سال انتشار: 1398
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 547
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شناسه ملی سند علمی:
JR_JADM-7-2_011
تاریخ نمایه سازی: 19 تیر 1398
چکیده مقاله:
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.
کلیدواژه ها:
نویسندگان
V. Babaiyan
Department Of Computer Engineering, Birjand University of Technology, Birjand, Iran.
Seyyede A. Sarfarazi
Department Of Computer Engineering, Birjand University of Technology, Birjand, Iran.