Decision-Making Analysis using Arduino-Based Electroencephalography (EEG): An Exploratory Study for Marketing Strategy

Abstract

Business technology has brought conventional marketing methods to the next level. These emerging integrated technologies has contributed to the growth and understanding of the consumer decision making process. Several studies have attempted to evaluate media content, especially on video advertising or TV commercials using various neuroimaging techniques such as the electroencephalography (EEG) device. Currently, the use of neuroscience in Malaysia's marketing research is very limited due to its limited adoption as an emerging technology in this field. This research uncovers the neuroscientific approach, particularly through the use of an EEG device; examining consumers' responses in terms of brain wave signals and cognition. A proposed theoretical framework on the factors affecting visual stimulus (movement, color, shape, and light) during the decision-making process by watching video advertising had been customized using two conceptual models of sensory stimulation. Ten respondents participated in the experiment to investigate the spectral changes of alpha brain wave signals detected in the occipital lobe. A 2-channel Arduinobased EEG device from Backyard Brains and Spike Recorder software was used to analyze the EEG signal through Fast Fourier Transform (FFT) method. Results obtained from the investigated population showed that there was statistically significant brain wave activity during the observation of the video advertising which demonstrated the interconnection with short-term memory through visual stimulus. Application of the neuroscience tool helped to explore consumer brain responses towards marketing stimuli with regards to the consumers' decision-making processes. This study manifests a useful tool for neuromarketing and concludes with a discussion, together with recommendations on the way forward.

A systematic review of the prediction of consumer preference using EEG measures and machine-learning in neuromarketing research

“…For example, a reduction in power in the alpha band (8–12 Hz) over occipital areas is generally considered to reflect visual processing. Occipital alpha-band power was found to be modulated by video but not print advertisements in early experiments [ 62 ], and has been used in more recent experiments to measure the visual processing of advertisement features [ 83 , 147 , 228 , 229 , 253 , 300 ].…”

[Retracted] Personalized Marketing Recommendation System of New Media Short Video Based on Deep Neural Network Data Fusion

“…(1) Create user data evaluation table: form users and n projects, obtain user setting functions based on the historical information of existing users and objects, and create an m * n evaluation board [7] (2) Calculate the user proximity set: based on the project-based user scoreboard, calculate the similarity between the target user and other users and use it as the basis for suggesting related projects [8].…”