  Neuromarketing aims to understand consumer behavior using neuroscience. Brain
imaging tools such as EEG have been used to better understand consumer behavior
that goes beyond self-report measures which can be a more accurate measure to
understand how and why consumers prefer choosing one product over another.
Previous studies have shown that consumer preferences can be effectively
predicted by understanding changes in evoked responses as captured by EEG.
However, understanding ordered preference of choices was not studied earlier.
In this study, we try to decipher the evoked responses using EEG while
participants were presented with naturalistic stimuli i.e. movie trailers.
Using Machine Learning tech niques to mine the patterns in EEG signals, we
predicted the movie rating with more than above-chance, 72% accuracy. Our
research shows that neural correlates can be an effective predictor of consumer
choices and can significantly enhance our understanding of consumer behavior.
