A 2-tuple Fuzzy Linguistic RFM Model and Its Implementation

Abstract

RFM is a model used to analyze the behavior of customer by means of three variables: Recency, Frequency and Monetary. The scores of these variables are expressed by an integer number, typically, in the range 1..5. The fuzzy linguistic approach is a tool intended for modeling qualitative information in a problem. In this paper, we propose to manage these RFM scores using the 2–tuple model which is a fuzzy linguistic model of information representation that carries out processes of “computing with words” without the loss of information. The proposed model permits us an easy linguistic interpretability and let us obtain a more precise representation of the RFM scores. Therefore, by interpreting these linguistic scores, decision makers can effectively identify valuable customers and consequently develop more effective marketing strategy. Additionally, we present an IBM SPSS Modeler implementation of this model. As a particular case study, we show an application example in order to select the customer of a loyalty campaign.