Multi-attribute market segmentation for the major customers of an Iranian steel-making company using value proposition elements

Abstract

Mass market strategy does not have a big chance for success in a competitive market. Therefore, by segmenting a heterogeneous market in to some smaller and homogenous markets in which customers have similar characteristics, it is expected that the resources can be more efficiently utilised. The purpose of this study was a mathematical modelling of market segmentation of an Iranian steel-making company using value proposition elements. The model mentioned was used for the analysis of data related to six value proposition elements from 129 major customers of the company. This model was solved using GAMS software and the optimal number of segments was 9. In this study, the results obtained were compared with those achieved by the conventional segmentation methods such as K-means and SOM and two-step clustering. Further, for the validation of the mathematical model used, discriminant analysis of research data was done after segmentation and the success percentage of the ranking rule was found to be 95.3%. Also, the similarity criterion was computed for each potentially new customer.