کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4946121 1439269 2017 22 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Statistics-based CRM approach via time series segmenting RFM on large scale data
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Statistics-based CRM approach via time series segmenting RFM on large scale data
چکیده انگلیسی
Conventional customer relationship management (CRM) is typically based on RFM model, whose parameters are the recency, frequency and monetary aspects of target customers. The latest comprehensive analysis has enabled CRM to present parameters with time series. For example, researchers can account for changing trends based on an RFM model for flexible marketing strategies. Such changes might inspire telecommunication service scenarios that user value relies on long-term performance. In this study, we propose a statistic-based approach to value latent users via time series segmenting time interval of RFM in large scale data set. Apart from utilizing in Spark platform, we integrate multiple corresponding analysis (MCA) to regularize clustering results by the RFM model and extend these approaches to multiple levels. A comprehensive set of experiments, revealed interesting observations regarding the co-existence of time interval and RFM model. First, the clustering method along time interval in three dimensions of the RFM model outperforms the method along the three dimensions in each interval. Subsequently, the cooperation of RFM and MCA provides a convenient methodology for exploring CRM in large-scale data. Therefore, the RFM model with time intervals integrated with MCA in CRM are essential.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 132, 15 September 2017, Pages 21-29
نویسندگان
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