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Data-mining application for country segmentation based on the RFM model
International Journal of Data Analysis Techniques and Strategies, 2008For effective Customer Relationship Management (CRM), it is important to gather information on customer value. Segmentation is the method of knowing the customers and partitioning a population of customers into smaller groups. This paper develops a novel country segmentation methodology based on Recency (R), Frequency (F) and Monetary value (M ...
Mehdi Ghazanfari +2 more
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A study of RFM-Customer satisfaction model for online purchasers
AIP Conference ProceedingsThe transaction data is underutilized after the e-commerce activity has successfully ended. This useful transactional data should be analyzed to discover some useful insights into the company to increase business performance.
Christine Ong Zi Qing, Lew Sook Ling
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Segmentaion of C2C Customer Using RFM Model
2011Customers segmentation is the key to customer relationship management, this paper analyze RFM (recency, frequency, and monetary value) paradigm with customer, and use RFM value as clustering properties by K-means. The customers can be divided into four levels includes important keep customers, important development customers, general customers ...
Jianying Xiong, Leiyue Yao
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Customer Segmentation Using Fuzzy-AHP and RFM Model
2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2020In today’s business environment the number of customers buying products online have increased, it is difficult for the firm to determine customer lifetime value (CLV) of every customer. In this paper, customer segmentation is used to find the customer lifetime value for a UK based registered company that sells unique gifts.
Anu Gupta Aggarwal, Sweta Yadav
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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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Fast RFM Model for Customer Segmentation
Companion Proceedings of the Web Conference 2022, 2022Shicheng Wan +4 more
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Customer lifetime value determination based on RFM model
Marketing Intelligence & Planning, 2016Purpose– One of the salient challenges in customer-oriented organizations is to recognize, segment and rank customers. Customer segmentation is usually based on customer lifetime value (CLV) measured by three purchase variables: “Recency,” “Frequency” and “Monetary.” However, due to the ambiguity of these variables, using deterministic approach is not ...
Fariba Safari +2 more
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APPLICATION OF RFM MODEL ON CUSTOMER SEGMENTATION IN DIGITAL MARKETING
Nigerian Journal of Science and EnvironmentCustomers playa pivotal role in the success of any business. The ability to attract and retain the right clientele, who consistently engage with a company's products and services, hinges on a thorough understanding of their purchasing behavior. Successful businesses tailor their offerings to meet the unique requirements and preferences
Maureen Akazue +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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IMPLEMENTATION OF RFM ANALYSIS USING SUPPORT VECTOR MACHINE MODEL
2018 2nd International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2018 2nd International Conference on, 2018In the modern business customer response is one of the vital characteristics of services. The customer relationship management accurately predict the invaluable customer. Because attention is needed to rate low response rating customers. Most of the direct marketing sectors randomly select and reduce degree of the influencing problem.
Ananthi Sheshasaayee, L. Logeshwari
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