The objective of the following work is to highlight the importance of categorical models applied to marketing strategies. In the past, multivariate statistical techniques were used for quantitative data in marketing decision support systems (MDSS), but there are many qualitative variables in present day marketing research, and the elaboration of these variables requires the use of categorical statistical models. In view of the scarcity of references in the literature to the contribution of applied categorical models to marketing, the scientific purpose of the present work involves the application of the methodology of categorical models to marketing management. A marketing information system (MIS) is an integrated structure involving people, equipment, and procedures which has the purpose of collecting, classifying, analyzing, evaluating and distributing relevant, timely and accurate data for operators making marketing decisions. In the management of marketing information systems, the utilization of statistical techniques is fundamental for the elaboration of data. In particular, the use of the following categorical statistical models is most useful: categorical regression model, categorical principal components model, non-linear canonical correlation model, multiple correspondences model, multidimensional scaling model. The categorical regression model is used to measure customers’ degree of satisfaction in relation to the use of some products or services. The categorical principle components model is used in the field of marketing to analyse the preferences or opinions on the characteristics of products expressed by consumers. The non-linear canonical correlation model makes it possible to measure the correlation between different sets of variables. The multiple correspondences model is used in marketing strategies for the creation of positioning maps for product brands through the opinions expressed by consumers on the qualities of the products. The multidimensional scaling model is used to analyse the perceptions and opinions expressed by consumers on the greater or lesser similarity between product brands.

The use of categorical statistical models in marketing information systems

FABIO MANCA
;
ANTONELLA MASSARI;FRANCESCO GIRONE
2015

Abstract

The objective of the following work is to highlight the importance of categorical models applied to marketing strategies. In the past, multivariate statistical techniques were used for quantitative data in marketing decision support systems (MDSS), but there are many qualitative variables in present day marketing research, and the elaboration of these variables requires the use of categorical statistical models. In view of the scarcity of references in the literature to the contribution of applied categorical models to marketing, the scientific purpose of the present work involves the application of the methodology of categorical models to marketing management. A marketing information system (MIS) is an integrated structure involving people, equipment, and procedures which has the purpose of collecting, classifying, analyzing, evaluating and distributing relevant, timely and accurate data for operators making marketing decisions. In the management of marketing information systems, the utilization of statistical techniques is fundamental for the elaboration of data. In particular, the use of the following categorical statistical models is most useful: categorical regression model, categorical principal components model, non-linear canonical correlation model, multiple correspondences model, multidimensional scaling model. The categorical regression model is used to measure customers’ degree of satisfaction in relation to the use of some products or services. The categorical principle components model is used in the field of marketing to analyse the preferences or opinions on the characteristics of products expressed by consumers. The non-linear canonical correlation model makes it possible to measure the correlation between different sets of variables. The multiple correspondences model is used in marketing strategies for the creation of positioning maps for product brands through the opinions expressed by consumers on the qualities of the products. The multidimensional scaling model is used to analyse the perceptions and opinions expressed by consumers on the greater or lesser similarity between product brands.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11586/279649
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