Journal Press India^®

Author Details ( * ) denotes Corresponding author

Purpose: The aim of this paper is to propose a matrix with dimensions or blocks of consumer segmentation while simultaneously presenting seven synthesized covariates.The aim is also to show its importance through rating the Rao, Chi-square, and Wald statistics, which have demonstrated how these statistics and their bases of segmentation can be used for the construction of different marketing models using binary logistic regression models. For this, the authors considered the binary criterion based on consumer purchase price or its counterpart i.e. product attributes as dependent variables. Two demographic covariates were identified; the psychographic covariate as well as the three behavioral covariate were identified.

Methodology: The treatment and compliance objectives in this research are guided by compliance to traditional econometric methodology, concretized through the model of binary logistic regression. Findings: The research shows that the matrix of dimensions and covariates are based on three behavioral dimensions that contribute more covariates of interest; expected benefits, brand awareness, and the customer’s loyalty to the brand. The demographic dimension favors the following variables: education and income. On the other hand, the psychographic block provides us with the consumer personality type variable. It must be noted that this classification was made individually, variable by variable. Once everything is incorporated into the study, some variables may have to leave the model. Thus, the essential importance of the behavioral characteristics manifested by the consumer in the process of binary discrimination purchase is brought to light.

Value: This paper shows the importance to develop prototypes for product differentiation based on segmentation criteria via binary choice models. The theoretical discourse of marketing in this topic has emphasized proper general aspects to recognize only guidelines addressing the topic of interest. It does so by presenting a source area for research and practice in the absence of models that come to contribute in a practical and concrete way to resolve shortcomings in this field of knowledge.

Keywords

Matrix Segmentation, Product Differentiation, and Binary Purchasing Criteria.

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