Principal Component Analysis - a powerful Tool in computing Marketing Information

Abstract

This paper is about instrumental research regarding a powerful multivariate data analysis method that can be used by researchers in order to obtain valuable information for decision-makers that need to solve the marketing problem a company face. The literature stresses the need to avoid the multicollinearity phenomenon in multivariate analysis and the features of Principal Component Analysis (PCA) in reducing the number of variables that could be correlated with each other to a small number of principal components that are uncorrelated. In this respect, the paper presents step-by-step the process of applying PCA in marketing research when we use a large number of variables that naturally are collinear.