VALID ESTIMATION OF PRICE IMPORTANCE WITH DUALSTAGE CONJOINT, MULTISTAGE CONJOINT FOR MULTI-LAYERED CAUSAL STRUCTURES

At IfaD, we know that price is often given a special degree of attention when making a purchase decision. That is why we use the Dualstage Conjoint for products with a large number of features, so that the price importance is correctly assessed. And we analyse complex structural models with a Multistage Conjoint, in which we embed individual Topic Conjoints into a superior Main Conjoint via anchor points.
A basic requirement for most conjoint methods, the linearity and independence of the product attributes, allows various Conjoints to be interlinked. Such interlinking is most effective when it is already done at the individual level, as this leaves open all of the different types of analysis options for conjoint data, such as segmentation and simulation.

VALID ESTIMATION OF PRICE IMPORTANCE WITH CONJOINT

In most conjoint studies, price occupies a special place. Often, all of the other attributes are compared to it (for example through the calculation of “monetary values”). Thus, the price is given a key position.
Price has a negative utility. This means that the higher its level, the lower will be the overall utility of the object under study. Price does not serve to describe any particular attribute of the object; rather it reflects the value that the consumer has to provide in order to pay for the overall utility delivered by the object’s various attributes. Because of this it stands in opposition to all the other attributes. This unique position occupied by price can lead to an underestimation of its importance, particularly as the number of attributes under study increases.
With a Dual Conjoint, two Conjoints are carried out within a single survey. The first Conjoint determines the relationship of the product attributes to one another (up to approximately 15 attributes can be studied). In the second Conjoint, a subgroup created from the first Conjoint is rated together with the price. The price is then embedded mathematically into the first (Attributes) Conjoint using the attributes which serve as anchor points, and which are used in both Conjoints.

STUDIES OF COMPLEX STRUCTURE MODELS WITH MULTISTAGE CONJOINT

With the help of a Multistage Conjoint, multi-layered causal structures can be examined, which can be broken down into clearly discernible topics. Each topic is asked in a single Conjoint. From the extreme points calculated from these specific Topic Conjoints, anchor points are derived, which are then used in a higher-level Main Conjoint. In addition to these anchor points, the Main Conjoint contains fundamental aspects of the object under study, such as price or brand. The results of the specific Topic Conjoints are embedded mathematically into the Main Conjoint, so that all of the attributes can be compared with all others.
Even highly comprehensive Structure Models with up to approx. 40 attributes can be studied. The risk of underestimating the price importance can be eliminated with the appropriate model design.

Multistage Conjoint

Multistage Conjoint: Care is paramount!

• A prerequisite for a Multistage Conjoint is that realistic assumptions are made regarding the model structure of the decision-making processes.
• The hierarchy levels have to be defined clearly. Allocating an attribute to the wrong level can result in its importance being over or underestimated.
• The topics must be clearly delimited and recognizable for the respondents. Artificial breakdowns threaten the validity of the findings.

MARKET SIMULATION WITH YOUR DUALSTAGE CONJOINT DATA AND YOUR MULTISTAGE CONJOINT DATA

MASIM is the ADABOX tool for running simulations based on Conjoint data. In addition to all common choice algorithms, MASIM contains further comprehensive functions, e.g. for product optimization and adjustment of models.