The technique of factor Analysis has multiple uses. They are:
Scale Construction: Factor Analysis is to be used to develop and design a concise multiple item scale for the measurement of various constructs. It is a part of exploratory research and Factor analysis helps in reducing the set of statements in more concise statements. The retained statements adequately represent the critical aspects of the constructs that are being measured.
Establish Antecedents: It helps to reduce the multiple input variables into more grouped variables. With factor analysis it is possible to group independent variables into broad factors.
Psychographic Profiling: The different independent variables are grouped together to measure the independent factors. They help in the identification of the personality types. The most famous example of this kind that has made use of the factor analysis is the 16 PF inventory.
Segmentation Analysis: It is possible to use factor analysis for the purpose of segmentation.
Marketing Studies: It has extensive use in the field of marketing as the name itself is indicative. It can be used for product development, acceptance research, advertising copy, pricing and many other as such.
Thus factor analysis has a very strong and useful role to play in the field of research. It has been used extensively and for many purposes by researchers doing research in various fields of expertise. Though its primarily famous as a data reduction technique but the above uses of factor analysis clearly indicate that it has its application in more than one functional area and has uses that spread beyond the fundamental use of being a data reduction technique and can contribute in creating a full-fledged research by itself that can help to give some conclusive output and aid the researcher in coming to some sound analysis.
The standard results of factor analysis can by interpret generally to include both principal components and principal factor analysis. To begin with, it is important to know in the formative stage itself to know how many factors to extract. At this stage it is not important to know the exact meaning of the factors, that is, what is the way to interpret them in a meaningful way. That can be done after the factors have been grouped into factors that segregated meanings can be attached to them.