EVALUATING NEUROMARKETING TECHNIQUE ON CONSUMER SATISFACTION USING EEG IMAGING

  • N.A. Mahamad
  • M.K.M. Amin
  • O. Mikami Tokai University, Japan
Keywords: Consumer Satisfaction, EEG

Abstract


This article presents an evaluation of consumer satisfaction using the EEG brain imaging technique. Involvement of brain science into marketing research has sparked great interest recently since traditional marketing solely dependent on questionnaires. Consumers are normally less cooperative with marketers when they made an unexplained decision by answering the questionnaires. In response to this problem, the EEG imaging technique could be used to identify the consumer response by analyzing their brain activities. A low-cost Emotiv EPOC EEG Neuroheadset was used in this experiment. Theta (ϑ) 4-8 Hz, Alpha (α) 8 to 12 Hz and Beta (β) 12-25 Hz waves are the basis for determining the brain activation. Popular shoes product advertisement on price reduction were displayed on the computer screen to observe the subject’s responses. The topographic maps result of the brain showed that the frontal lobe and the right part of the brain activated the most which indicates the contentment or satisfaction behaviour. Further analysis on the power spectral density showed that higher synchronization of Theta (ϑ), Alpha (α) and Beta (β) bands were more apparent in the right frontal lobe which thus confirmed a significant correlation of marketing decisions with the brain activities.

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Author Biography

O. Mikami, Tokai University, Japan

2Department of Optical and Imaging Science & Technology,

School of Engineering, Tokai University,

Hiratsuka, Kanagawa, 259-1292 Japan.

References

[1] R.N. Khushaba, C. Wise, S. Kodagoda, J. Louviere, B.E. Kahn and C. Townsend "Consumer neuroscience: assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking”, Expert Systems with Applications, vol. 40, no. 9, pp. 3803-3812, 2013.

[2] V.A. Roth, “The potential of neuromarketing as a marketing tool”, Bachelor thesis, Faculty of Management and Governance, University of Twente, Netherlands, 2014.

[3] R. Dooley, Brainfluence: 100 ways to persuade and convince consumers with neuromarketing. New Jersey: John Wiley & Sons, 2012.

[4] V. Sebastian, "Neuromarketing and evaluation of cognitive and emotional responses of consumers to marketing stimuli”, Procedia-Social and Behavioral Sciences, vol. 127, pp. 753-757, 2014.

[5] J.G. Vargas-Hernandez and A.A. Burgos-Campero, “Analytical approach to neuromarketing as a business strategy, Journal of Euromarketing, vol. 22, pp. 64-73, 2013.

[6] F. Babiloni, “Consumer neuroscience: A new area of study for biomedical engineers”, IEEE Pulse, vol. 3, no. 3, pp. 21-23, 2012.

[7] S. Darafsheh. (2017). How does brain sensing technology work? [Online]. Available: https://www.iotforall.com/brain-sensing-technology-muse-headband/

[8] iMOTIONS. (2019). Electroencephalography (EEG) [Online]. Available: https://imotions.com/guides/electroencephalography-eeg/

[9] Y.Y. Lee and S. Hsieh, “Classifying different emotional states by means of EEG based functional connectivity patterns,” PLoS ONE, vol. 9, no. 4, pp. 1-13, 2014.

[10] W.Y. Hsu, "An integrated-mental brainwave system for analyses and judgments of consumer preference”, Telematics and Informatics, vol. 34, no. 5, pp. 518-526, 2017.

[11] Y. Liu, O. Sourina and M.R. Hafiyyandi, “EEG-based emotion-adaptive advertising,” in Humaine Association Conference on Affective Computing and Intelligent Interaction, Geneva, Switzerland, 2013, pp. 843-848.

[12] N. Jalaudin and M.K.M. Amin, “EEG analysis on human reflection towards relaxation of mind,” Malaysian Journal of Fundamental and Applied Sciences, vol. 15, no. 2, pp. 185-189, 2019.

[13] M. Yadava, P. Kumar, R. Saini, P.P. Roy and D.P. Dogra, "Analysis of EEG signals and its application to neuromarketing”, Multimedia Tools and Applications, vol. 76, no. 18, pp. 19087-19111, 2017.

[14] R. Ohme, D. Reykowska, D. Wiener and A. Choromanska, "Application of frontal EEG asymmetry to advertising research”, Journal of Economic Psychology, vol. 31, no. 5, pp. 785-793, 2010.

[15] N. Behboodin, M. Kamal, K. Natsume and T. Kitajima, “Frequency analysis of brain signals for biometric application,” International Journal of Pure and Applied Mathematics, vol. 118, no. 24, pp. 1-14, 2018.

[16] Trans Cranial Technologies Ltd. (2012). 10/20 System Positioning Manual [Online]. Available: http://chgd.umich.edu/wp-content/uploads/2014/
06/10-20_system_positioning.pdf

[17] S.P. Kvaale, “Emotion recognition in EEG: A neuroevolutionary approach,” M.S. thesis, Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway, 2012.

[18] TechSmith Corporation. (2019). Camtasia: Screen Recorder and
Video Editor [Online]. Available: https://www.techsmith.com/video-editor.html

[19] A.N. Alshbatat, P.J. Vial, P. Premaratne and L.C. Tran., "EEG-based brain-computer interface for automating home appliances”, Journal of Computers, vol. 9, no. 9, pp. 2159-2166, 2014.

[20] Nike, Inc. (2019). Nike Joyride Dual Run [Online]. Available: https://www.nike.com/my/
Published
2019-12-28
How to Cite
Mahamad, N., Amin, M., & Mikami, O. (2019). EVALUATING NEUROMARKETING TECHNIQUE ON CONSUMER SATISFACTION USING EEG IMAGING. Journal of Advanced Manufacturing Technology (JAMT), 13(2(2). Retrieved from https://jamt.utem.edu.my/jamt/article/view/5716
Section
Articles

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