Discriminant Analysis allows a researcher to study the difference between two or more groups of objects with respect to several variables simultaneously, determining whether meaningful differences exist between the groups and identifying the discriminating power of each variable.
For example, a research company may want to investigate which variables discriminate between customers who decide:
(1) To buy branded products,
(2) To buy non-branded products
For that purpose the researcher could collect data on numerous variables. All the shoppers will naturally fall into one of the two categories. An explanatory use of discriminant function analysis can provide insight into which variables are most significantly associated with shoppers who go to market. The variables may be age, sex, profession, earnings, etc. Based on these, the companies can use the information and apply it to predict the buying behaviour of customers to price their product, design product according to their needs.
Therefore, Discriminant Analysis is a very useful tool
(1) for detecting the variables that allow the researcher to discriminate between different groups, and
(2) for classifying cases into different groups with a better than chance accuracy.