One assumption inherent in adaptive and tradition conjoint analysis is pair-wise independence of attributes — that the importance of a product feature is not dependent on any other feature. If true, then the part-worth of the attributes is additive.
While the pair-wise independence assumption is valid most of the time, it is unlikely to hold true for brand and price. Some brands are more sensitive to changes in price than others. The importance of price, therefore, depends on the brand with which it is associated.
Traditional conjoint assumes a single price utility function, but in reality the function would differ for each brand.
When two attributes are pairwise dependent, we say that there is statistical interaction between the attributes. This is handled by adding the interaction term, price × brand, to the utility model.
A model which fails to capture this interaction, would essentially get the price sensitivity wrong.
Note: To find content on MarketingMind type the acronym ‘MM’ followed by your query into the search bar. For example, if you enter ‘mm consumer analytics’ into Chrome’s search bar, relevant pages from MarketingMind will appear in Google’s result pages.