Services on Demand
Journal
Article
Indicators
- Cited by SciELO
- Access statistics
Related links
- Cited by Google
- Similars in SciELO
- Similars in Google
Share
Tecnura
Print version ISSN 0123-921X
Abstract
CUADROS LOPEZ, Álvaro Julio; GONZALES CAICEDO, Caterine and JIMENEZ OVIEDO, Paola Cristina. Multivariate analysis for customer segmentation based on RFM. Tecnura [online]. 2017, vol.21, n.54, pp.41-51. ISSN 0123-921X. https://doi.org/10.14483/22487638.12957.
Context:
To build a successful relationship management (CRM), companies must start with the identification of the true value of customers, as this provides basic information to implement more targeted and customized marketing strategies. The RFM methodology, a classic analysis tool that uses three evaluation parameters, allows companies to understand customer behavior, and to establish customer segments. The addition of a new parameter in the traditional technique is an opportunity to refine the possible outcomes of a customer segmentation since it not only provides a new element of evaluation to identify the most valuable customers, but it also makes it possible to differentiate and get to know customers even better.
Method:
The article presents a methodology that allows to establish customer segments using an extended RFM method with new variables, selected through multivariate analysis..
Results:
The proposed implementation was applied in a company in which variables such as profit, profit percentage, and billing due date were tested. Therefore, it was possible to establish a more detailed customer segmentation than with the classic RFM.
Conclusions:
the RFM analysis is a method widely used in the industry for its easy understanding and applicability. However, it can be improved with the use of statistical procedures and new variables, which will allow companies to have deeper information about the behavior of the clients, and will facilitate the design of specific marketing strategies.
Keywords : CRM; Multivariate analysis; RFM; Segmentation.