The Effect of Measurement Task Transparency on Preference Construction and Evaluations of Personalized Recommendations

Abstract

Marketing activities frequently involve personalizing product offers to consumers' individually measured preferences. Because preferences are often ill-defined, responses to customized offers may depend on how easy it is for consumers to identify the preferences they stated in the measurement task. A series of experiments shows that the likelihood of choosing a personalized recommendation that matches measured preferences most closely is greater with measurement tasks that allow consumers to identify their stated preferences more easily (i.e., transparent tasks). However, this difference in choice likelihood due to task transparency is observed only for novices (versus experts), and making the identification of stated preferences more difficult eliminates the effect by decreasing the choice likelihood following more (versus less) transparent tasks. The author identifies consumers' understanding of their own preferences as the mechanism underlying the task transparency effect. The findings provide evidence that consumers must be able to “see through” or understand the construction of their preferences to maximize utility.