In many cases, relying only on consumers’ verbal reports or their responses to questionnaires for evaluation of their preferences can result in biased, inaccurate or inconclusive results. Therefore, we employ various neural and physiological measurements (such as fMRI, EEG, GSR, EMG and eye-tracking) to acquire information about consumer’s preferences that is unobtainable through conventional methods. Mainly, we obtain neural and physiological data while consumers evaluate various related marketing campaigns (such as TV ads, internet pages, pictures, etc.), extract multiple measurements from the recordings, and try to predict consumers’ future choices and behavior using diverse machine & deep learning approaches. We aspire to increase the predictive power currently attainable with standard non-physiological measures and to identify consumers’ true preferences — namely the choice they will make at the time of their purchasing decision.