Using EEG to Predict Consumers’ Future Choices

Abstract

It is well established that neural imaging technology can predict preferences for consumer products. However, the applicability of this method to consumer marketing research remains uncertain, partly because of the expense required. In this article, the authors demonstrate that neural measurements made with a relatively low-cost and widely available measurement method—electroencephalography (EEG)—can predict future choices of consumer products. In the experiment, participants viewed individual consumer products in isolation, without making any actual choices, while their neural activity was measured with EEG. At the end of the experiment, participants were offered choices between pairs of the same products. The authors find that neural activity measured from a midfrontal electrode displays an increase in the N200 component and a weaker theta band power that correlates with a more preferred product. Using recent techniques for relating neural measurements to choice prediction, they demonstrate that these measures predict subsequent choices. Moreover, the accuracy of prediction depends on both the ordinal and cardinal distance of the EEG data; the larger the difference in EEG activity between two products, the better the predictive accuracy.