When users assess or choose products and services, such processes always depend on a range of different features. If you only take the overall evaluation into consideration, you may know how good or bad the consumer finds the product or service to be; however, how the assessment was made or what factors play a role in the evaluation remain unknown.

What lies behind the evaluation cannot be seen. This is true not only for products but also with regard to aspects such as customer and employee satisfaction.

This is where regression analyses can be applied, as they can be considered as a type of driver analysis. They present a model of the influence individual characteristics and factors have on the overall assessment or show the strength of various influencing factors may have on a (discrete) decision.

Given that the questions are applied separately to the assessment of individual characteristics, their influence can be determined independently of the respondents’ conscious perception. This can be beneficial since people subjectively tend to distort their perceptions if they are asked to describe the significance or importance of individual characteristics.