Conjoint Analysis – Meaning, Usage and its Limitations
February 12, 2025
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Factor Analysis is a data reduction technique. Given a large number of attributes, factor analysis identifies a few underlying dimensions by grouping the attributes based on the correlation between the attributes. For example, price of a product, the cost after sales service, and maintenance expense can be identified as a part of single dimension: Total Cost
Attributes such as Insomnia, Nausea and Suicidal Tendency can be collectively described by a single term: Depression. Here three variables/attributes have been represented by a single factor.
Factor analysis is usually more meaningful when it is followed by subsequent procedures such as clustering. Following are some of the applications of this method:
While factor analysis is used in several fields such as psychometrics, psychology, physical sciences, etc, we will focus on the topic relevant in this module: marketing research. The procedure for utilizing factor analysis in a typical marketing research study is as follows:
Industry examples requiring usage of this tool
For this method to be valid, certain assumptions must hold true:
Var1 | Var2 | Var3 |
1 | 2 | 3 |
2 | 4 | 6 |
3 | 6 | 9 |
4 | 8 | 12 |
Each variable must be unique. Var2 and Var3 can be reduced to Var1 by dividing them by numbers 2 and 3 respectively. Since they are basically the same data sets, they cannot be used for forming factors.
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