A Fuzzy Linguistic RFM Model Applied to Campaign Management
Metadatos
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Carrasco, Ramón Alberto; Blasco, María Francisca; García-Madariaga, Jesús; Herrera Viedma, EnriqueEditorial
IMAI Software
Fecha
2018-03-23Referencia bibliográfica
Alberto Carrasco, R., Francisca Blasco, M., García-Madariaga, J., & Herrera-Viedma, E. (2019). A Fuzzy Linguistic RFM Model Applied to Campaign Management. International Journal of Interactive Multimedia & Artificial Intelligence, 5(4).
Patrocinador
This paper has been elaborated with the financing of FEDER funds in the Spanish National research project (TIN2013-40658-P), Spanish Department for Economy and Competitiveness project (TIN2016- 75850-R).Resumen
In the literature there are some proposals for integrated schemes for campaign management based on segmentation
from the results of the RFM model. RFM is a technique used to analyze customer behavior by means of three
variables: Recency, Frequency and Monetary value. It is s very much in use in the business world due to its
simplicity of use, implementation and interpretability of its results. However, RFM applications to campaign
management present known limitations like the lack of precision because the scores of these variables are
expressed by an ordinal scale. In this paper, we propose to link customer segmentation methods with campaign
activities in a more effective way incorporating the 2–tuple model both to the RFM calculation process and to
its subsequent exploitation by means of segmentation algorithms, specifically, k-means. This yields a greater
interpretability of these results and also allows computing these values without loss of information. Therefore,
marketers can effectively develop more effective marketing strategy.