Factor analysis: Definition, sample questions

Factor analysis helps you in condensing variables and uncovering clusters of responses. Let us look at how it actually works with an example scenario:

You decide to ask some questions like below that cover somewhat similar grounds of customer satisfaction –  

1. How did you like our product?
2. Will you consider referring us to your friends and family? 

As for evaluating the entire performance of the organization, it would be convenient for you to have only one variable that represents the customer experience score. It can be done in two ways:

• Get an average of both the questions
• Run a PCA (Primary Component Analysis) and have a factor dependent variable. 

PCA technique is generally more effective than the average method as it calculated the weightage of the variables along with the calculations. 

There might be a case where you want to ask several questions to the customer but don’t exactly know which responses can be grouped together and which will be kept totally different. Example: purchase barriers of the target customers. The reasons for the same could be:

1. Price is prohibitive
2. Overall implementation costs
3. We can’t reach a consensus in our organisation
4. Product is not consistent with our business strategy
5. I need to develop an ROI, but cannot or have not
6. We are locked into a contract with another product
7. The product benefits don’t outweigh the cost
8. We have no reason to switch
9. Our IT department cannot support your product
10. We do not have sufficient technical resources
11. Your product does not have a feature we require
12. Other (please specify)

Factor analysis helps you to group these responses like: