The aim of conjoint analysis is to be able to assess the customer’s acceptance of a product and its functions.
For this purpose, different variants of a product are presented to the customers, who rank them according to weighted customer requirements with regard to the individual product features.
Subsequently, customer-oriented utility values for the individual characteristic values are obtained from this, for example by means of mathematical-statistical iteration and simulation procedures.
As a rule, it is assumed that the total benefit is composed additively of the benefit of the individual characteristic values. To perform conjoint analysis, you need different product variants, weighted customer requirements and a sufficiently large group of subjects.
Example: For a bicycle manufacturer, it would be important to determine what significance the characteristics “manufacturer”, “gear shift” and “color of the bicycle” have for the user’s purchase decision. A conjoint analysis would combine total products consisting of different features (for example, a blue Giant bike with a 21-speed and a red Hercules bike with a seven-speed and so on).
The respondent now votes on each of these overall concepts. Within the framework of the conjoint procedure, it is possible to infer the user’s preferences with regard to the individual characteristics and characteristic values from the information provided by the user. In our example, it could result that the manufacturer is mainly responsible for the benefit of the bicycle as perceived by the customer. With the help of current information technology, it is now possible to present such alternatives as virtual two- and three-dimensional models.
The advantage of this method over other methods (market surveys, customer surveys and so on) is that the relevance of various product features in the purchase process can be revealed by the customer.