The Reference Forward Model (RFM)

Future Budget Allocation Model (RFM) –Principles, models and incentives

Customer Lifetime Value (CLV) Measurement Based on RFM Model

Nowadays companies increasingly derive revenue from the creation and sustenance of long-term relationships with their customers. In such an environment, marketing serves the purpose of maximizing customer lifetime value (CLV) and customer equity, which is the sum of the lifetime values of the company’s customers. A frequently-encountered difficulty for companies wishing to measure customer prof...

Invariant pattern recognition using the RFM descriptor

A pattern descriptor invariant to rotation, scaling, translation (RST), and robust to additive noise is proposed by using the Radon, Fourier, and Mellin transforms. The Radon transform converts the RST transformations applied on a pattern into transformations in the radial and angular slices of the Radon transform data. These beneficial properties of the Radon transform make it an useful interm...

Optimization of the Complex-RFM Optimization Algorithm

This paper presents and compares different modifications made to the ComplexRF optimization algorithm with the aim of improving its performance for computationally expensive models with few variables. The modifications reduce the required number of objective function evaluations by creating and using surrogate models of the objective function iteratively during the optimization process. The cho...

Visualizing RFM Segmentation

Segmentation based on RFM (Recency, Frequency, and Monetary) has been used for over 50 years by direct marketers to target a subset of their customers, save mailing costs, and improve profits. RFM analysis is commonly performed using the Arthur Hughes method, which bins each of the three RFM attributes independently into five equal frequency bins. The resulting 125 cells are depicted in a tabul...