Discriminant analysis - An efficient tool in Research – Oriented Applications

The blog is on the basis of inputs given on Discriminant analysis and its relevance in Perceptual Mapping in Market Research projects.

Starting off with an example about, how a manufacturer of a salon brand hair care item, could find out if demographic variables, like, education level, ethnicity, personal income, sex and a number of other factors are useful in distinguishing purchasers of their products from purchasers of other salon hair care brands.

Discriminant Analysis is an efficient market segmentation technique because of its ability to classify individuals or experimental units into two or more uniquely defined populations. The discriminant score is the basis for predicting to which group (a purchaser of the manufacturer’s brand or a competitive brand) the particular individual belongs. The discriminant weights of each predictive variable (age, sex, income, etc) indicate the relative importance of each variable. For instance, if age has a low discriminant weight then it is less important than the other variables.

Following the example, which illustrated how discriminant analysis helped classify users and nonusers of salon brand hair care products based on independent variables, other uses of discriminant analysis include the following:
Product research – Distinguish between heavy, medium, and light users of a product in terms of their consumption habits and lifestyles
Perception/Image research – Distinguish between customers who exhibit favorable perceptions of a store or company and those who do not
Advertising research – Identify how market segments differ in media consumption habitsDirect marketing – Identify the characteristics of consumers who will respond to a direct marketing campaign and those who will not.

Submitted By:
Veena Viswanath
Roll No: 12055