A Data Mining System for Enhancing Profit Growth based on RFM and CLV

Understanding customer has piqued the curiosity of industry experts, marketing executive’s and academics researchers. The potential value of a customer to a business can be a key factor in decision making. Customers assessment, identifying the differences between them, and ranking them is one of the major issues in customer-based enterprises. However, leveraging all of our strengths, as well as new technologies such as machine learning algorithms and data treatment, we can now build very powerful models that allows us to better understand consumer requirements and behaviors, and respond properly to meet his demands. In the present paper, we propose a model based on Customer Lifetime Value (CLV) and the Recency, Frequency and Monetary (RFM) model to address these concerns. This model will assist us in gaining a clear understanding of our consumer categories and determining what actions we can take for each category.