A gateway to consumers' minds: Achievements, caveats, and prospects of electroencephalography‐based prediction in neuromarketing. Issue 2 (29th November 2018)

• Record Type: Journal Article
• Authors: Hakim, Adam; Levy, Dino J.
• Is Part Of: Wiley interdisciplinary reviews. Volume 10:Issue 2(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-11-29
• Subjects: consumer neuroscience -- EEG -- neuromarketing -- prediction; Cognitive science -- Periodicals; 153.05
• DOI: 10.1002/wcs.1485
• Languages: English
• ISSNs: 1939-5086

Abstract

Abstract : In the last decade, the field of consumer neuroscience, or neuromarketing, has been flourishing, with numerous publications, academic programs, initiatives, and companies. The demand for objective neural measures to quantify consumers' preferences and predict responses to marketing campaigns is ever on the rise, particularly due to the limitations of traditional marketing techniques, such as questionnaires, focus groups, and interviews. However, research has yet to converge on a unified methodology or conclusive results that can be applied in the industry. In this review, we present the potential of electroencephalography (EEG)‐based preference prediction. We summarize previous EEG research and propose features which have shown promise in capturing the consumers' evaluation process, including components acquired from an event‐related potential design, inter‐subject correlations, hemispheric asymmetry, and various spectral band powers. Next, we review the latest findings on attempts to predict preferences based on various features of the EEG signal. Finally, we conclude with several recommended guidelines for prediction. Chiefly, we stress the need to demonstrate that neural measures contribute to preference prediction beyond what traditional measures already provide. Second, prediction studies in neuromarketing should adopt the standard practices and methodology used in data science and prediction modeling that is common in other fields such as computer science and engineering. This article is categorized under: Economics > Interactive Decision‐Making Economics > Individual Decision‐Making Psychology > Prediction Neuroscience > Cognition Abstract : EEG‐based preference predictions have the potential for substantial contribution to marketing success.