Like/Dislike Prediction for Sport Shoes With Electroencephalography: An Application of Neuromarketing.

Li Zeng,Hui Zhou,Mengsi Lin,Keyang Xiao,Jigan Wang

doi:10.3389/fnhum.2021.793952

Li Zeng, Hui Zhou + Show 3 more

Open Access

https://doi.org/10.3389/fnhum.2021.793952

Copy DOI

Abstract

Neuromarketing is an emerging research field for prospective businesses on consumer’s preference. Consumer’s preference prediction based on electroencephalography (EEG) can reliably predict likes or dislikes of a product. However, the current EEG prediction and classification accuracy have yet to reach ideal level. In addition, it is still unclear how different brain region information and different features such as power spectral density, brain asymmetry, differential entropy, and Hjorth parameters affect the prediction accuracy. Our study shows that by taking footwear products as an example, the recognition accuracy of product likes or dislikes reaches 94.22%. Compared with other brain regions, the features of the frontal and occipital brain region obtained a higher prediction accuracy, but the fusion of the features of the whole brain region could improve the prediction accuracy of likes or dislikes even further. Future work would be done to correlate the EEG-based like or dislike prediction results with product sales and self-reports.

Highlights

Neuromarketing is an emerging interdisciplinary research area that aims to understand biology of consumer’s behavior by integrating neuroscience with marketing, which can decipher consumers’ unrevealed preferences, motivations, and decisions by measuring their physiological and neural signals (Ariely and Berns, 2010; Morin, 2011; Aldayel et al, 2020; Bazzani et al, 2020)
The purpose of this study is to design a product like or dislike prediction system based on EEG using commonly worn sport shoes as product example, so that comparison of the characteristics of consumer’s preference of commonly used EEG in published literature can be made and to compare the classification accuracy of these features
The EEG-based consumer’s like or dislike prediction system demonstrated in this work achieved a classification accuracy of 94.22% using Differential entropy (DE) features

Summary

Introduction

Neuromarketing is an emerging interdisciplinary research area that aims to understand biology of consumer’s behavior by integrating neuroscience with marketing, which can decipher consumers’ unrevealed preferences, motivations, and decisions by measuring their physiological and neural signals (Ariely and Berns, 2010; Morin, 2011; Aldayel et al, 2020; Bazzani et al, 2020). Conventional marketing provides only relative analysis of consumer’s response, which relies on conducting surveys, interviews, running focus groups, and field trials for collecting consumer’s feedback. These analysis approaches suffer limitations due to high cost, time requirement, and untrustworthy information. Conventional approaches have significant inherent weaknesses arising from consumers not always forthcoming about their feelings and preferences. All of these drawbacks would lead to biased or inaccurate conclusions (Khushaba et al, 2012; Boksem and Smidts, 2015). Compared with conventional marketing research techniques, neuromarketing empowers researchers to capture consumers’ intricate neural processes to a range of marketing stimuli with moment-to-moment neural data, allowing to forecast consumer’s decision-making, like–dislike, and purchase decisions with greatly improved accuracy (Venkatraman et al, 2012; Barnett and Cerf, 2017; Bell et al, 2018; Goto et al, 2019)

Objectives

Methods

Results

Discussion

Conclusion