Simulation of Purchase Decision Situations    

The conjoint analysis permits a simulation of purchase decision situations. Here, the prices for complex products and use values for the individual components can be determined. The evaluation offers the opportunity to cost market simulations and to demonstrate which product configurations have the best chances on the market or even to what extent new products can oust products already established on the market.
Conjoint analyses can be used both for products (e.g. fast-moving consumer goods) and for services. However, it must be possible to break these down into qualities relevant to purchase decisions, which can be adjusted in their form. In addition, the product or service alternatives available must be presented to those questioned in as realistic a way as possible.    

Zoom: The respondents have to choose one of the three telecommunication bundles, or select “No purchase”. The components of the bundles (light cells in the table) including prices are randomly generated for each task.

The table shows an example of how the Choice-Based Conjoint can be queried: The respondents have to choose one of the three telecommunication bundles, or select “No purchase”. The components of the bundles (light cells in the table) including prices are randomly generated for each task. This task is shown in Choice Based Conjoint (CBC, please see below) up to 20 times with changing content.

When is a conjoint analysis appropriate?

With complex products or services composed of several sub-properties.

Furthermore, there should be alternatives to these properties (thus a tablet PC could have various different screen sizes and storage capacities). The conjoint analysis identifies the relative values of each of these properties (partial benefit) and can pinpoint the optimum price for the relevant overall product (sum of all the partial benefits).

We apply the following conjoint analyses first and foremost:

Choice-Based Conjoint Analysis (CBC): In choice-based conjoint, the persons questioned have to choose one of two, three, four or even more products described in detail and presented on one page (discreet choice approach). Since they also have the possibility of deciding against all the products presented (no-choice option) and thus not selecting a product at all, the survey is very similar to a real-life decision-making situation. In CBC, this selection task is presented up to 20 times with varying content.

Adaptive Conjoint Analysis (ACA): In CBC, the people questioned are presented with quick and demanding decision-making tasks, even if the products to choose from are only described with a few characteristics. An upper limit of six features should therefore not be exceeded. If more characteristics need to be used, then adaptive conjoint analysis (ACA) is an option. This is broken down into a conventional section, in which the importance of the properties is surveyed, and an actual conjoint section, in which sample sets of properties are put together and presented to those questioned for selection.

Adaptive Choice-Based Conjoint (ACBC): Whilst with CBC the product alternatives shown to respondents are not aimed at personal product preferences, the ACBC process offers the opportunity to adapt the products presented to respondents’ preferences. It consists of numerous individual steps, whose content gradually helps to reveal the preference structure of the respondent. The ACBC process is significantly longer than a normal CBC. For this reason, respondents generally find the ACBC process to be more interesting and more involving.

Zoom: The conjoint processes permit a simulation of purchase decision situations with complex products comprising various different components.
The result enables us to estimate the sales of different products.

The example graph shows the following: The attractiveness of the offer is generally high. The maximum estimated sales can be achieved at a price between 80 and 95 CHF,
since there are a sufficient proportion of customers, who would be willing to buy the product at a higher price.