MULTIPLE CORRESPONDENCE ANALYSIS FOR CUSTOMER SEGMENTATION IN LARGE RETAIL GROUPS.

The aim of the following work is to highlight the importance of categorical methods as applied to marketing strategies. In the past, multivariate statisti- cal techniques were used for quantitative data in marketing decision support systems (MDSS), however, given the introduction of many categorical vari- ables in present day marketing research, the elaboration of these variables requires the use of categorical statistical methods. In order to carry out this research, we have employed multiple correspon- dence analysis, which, by means of maps constructed on a limited number of latent dimentions, simplies the reading of both the intricate relations among the numerous categorical variables observed and their categories. In market research on the purchasing behavior of consumers, these analyses have been used to determine the essential aspects of consumer behavior as a rational basis for adopting opportune marketing strategies.