Maximum Difference Scaling: Finding preferences made easy
Maximum Difference Scaling (MaxDiff) is a highly efficient method to determine preference differences between a relatively large – theoretically even unlimited – number of similar stimuli or attributes. It works similar to a simple paired comparison.
Questions for which MaxDiff is suitable are, for example, which product features have the highest relevance for the purchase decision, which features are best suited to a brand or a product, or which benefits or claims have the highest significance for communication or advertising.
Questions that can be addressed with the MaxDiff method are, for example, “Which product features have the highest relevance for purchase intention?” or, “Which features have the highest brand or product fit?” or, “Which benefits or claims have the strongest impact in communication or advertisement?”
Usually, the above questions are answered with scaled applicability or rankings (“fits best” etc.). These techniques do have some known weaknesses, however:
Scaled ratings are usually not selective enough (i.e. you get similar values for all stimuli). Moreover, they are prone to unidirectional answer tendencies like, for example, simplification, social desirability and cultural effects (in one country people prefer characteristic differences more than in another), to mention just the most important.
Rankings, are usually limited to a small number of stimuli.