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Personalized Dynamic Pricing with RFM Modeling
Proceedings of the 2021 7th International Conference on e-Society, e-Learning and e-Technologies, 2021Dimitrios Kelesakis +2 more
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Study of Customer Value and Supplier Dependence with the RFM Model
2015In this study, data mining is applied to the use of an Enterprise Resource Planning (ERP) database to explore the core value of business operations by revising the RFM model into an RFGP model through “customer value analysis”. This model is used as a tool by enterprises to make proper adjustment to business strategies in a timely manner.
Jui-Hung Kao +3 more
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A Customer Segmentation Model Proposal for Retailers: RFM-V
2021Today's businesses have large quantity of demographic, economic and behavioral data on their customers with the rapid development of computer and internet technologies. Customer segmentation analyzes are carried out on the basis of various parameters in order to identify and group consumers with different needs and wishes and to develop marketing ...
Özkan, Pınar, Deveci Kocakoç, İpek
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Dynamic Models for RFM Variables: A Forward Looking Approach
2015On the database marketing literature, it is common practice to summarize customers’ past behavior in terms of their Recency, Frequency and Monetary Value (RFM) characteristics. Recency is the time of most recent purchase, Frequency is the number of past purchases and Monetary Value is the average purchased amount per transaction.
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Customer Behavior Analytics in A Supermarket in Taiwan Based on RFM Model
International Journal of Industrial and Systems Engineering, 2023Mei Wei Huang +4 more
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Rfm Model Customer Segmentation Based on Hierarchical Approach Using Fca
Expert Systems with Applications, 2023Chongkolnee Rungruang +4 more
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Customer Segmentation with RFM Analysis using ML Models
2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), 2023Manpreet Kaur +4 more
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Applied Marketing Analytics: The Peer-Reviewed Journal
Customer segmentation is important for marketing and campaign management, and the RFM (recency, frequency and monetary) model is widely used for this purpose. However, existing algorithms typically segment customers based on overall similarity in R, F and M scores, which may not provide the most meaningful insights for retailers.
A. Joy Christy +2 more
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Customer segmentation is important for marketing and campaign management, and the RFM (recency, frequency and monetary) model is widely used for this purpose. However, existing algorithms typically segment customers based on overall similarity in R, F and M scores, which may not provide the most meaningful insights for retailers.
A. Joy Christy +2 more
openaire +1 more source
Predicting customer value per product: From RFM to RFM/P
Journal of Business Research, 2021Cleo Schmitt Silveira
exaly