DeePay: deep learning decodes EEG to predict consumer's willingness to pay for neuromarketing.

ABSTRACT: There is an increasing demand within consumer-neuroscience (or neuromarketing) for objective neural measures to quantify consumers' subjective valuations and predict responses to marketing campaigns. However, the properties of EEG raise difficulties for these aims: small datasets, high dimensionality, elaborate manual feature extraction, intrinsic noise, and between-subject variations. We aimed to overcome these limitations by combining unique techniques of Deep Learning Networks (DLNs), while providing interpretable results for neuroscientific and decision-making insight. In this study, we developed a DLN to predict subjects' willingness to pay (WTP) based on their EEG data. In each trial, 213 subjects observed a product's image, from 72 possible products, and then reported their WTP for

SUBMITTER: Hakim A 

PROVIDER: S-EPMC10277553 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature