Factor Analysis has proven to be a very useful technique in the field of market research and analysis. Its various uses are:
• It helps to make sense of a big data which has interlinked relationships
• It helps to decipher relationships that have been hidden
• It helps to surface up the underlying relationship that is there between tastes preferences of consumers where factor analysis is largely used.
• It helps in the condensing of the data
• It helps in correlating the data and draw conclusions from the gathered data.
• Helps in formation of the empirical clusters.
Types of Factor Analysis:
The larger use of factor analysis is for understanding the interpretation of data and analysing the underlying relationship that exists between variables and the other underlying factors. Factor analysis works beyond grouping responses and their types; on the other hand it segregates the variables and then groups them according to their co relevance.
Factor Analysis can largely be segregated into three categories, depending upon its varied use in the market.
• Exploratory Factor Analysis
• Confirmatory Factor Analysis
• Structural Equation Modelling
The exploratory factor analysis is used for the measurement of the underlying factors that have an effect on the variables in the data structure. This is done without any biased perspective and setting a pre-defined structure to the outcome. The second kind of factor analysis, which is the confirmatory factor analysis is used to confirm the correlation in the existing set of the factor that have been predefined and the different variables that affect these factors. The third type of factor analysis which is called the structural modelling hypothesises the relationship between a set of variables. It can be used for both exploratory as well as confirmatory modelling.
Factor analysis would yield accurate and beneficial results only when the expertise of the researcher is there in selecting the data and assigning it the attributes. Choosing of the correct factors so as to avoid a lot of overlapping in characteristics is also very important. If done in the right manner, factor analysis would assist in very critical decision making. It is particularly useful in consumer behaviour studies and it woyld help in product development, pricing segmentation, penetration, distribution, pricing and other important decisions.
