Marketing and Management of Innovations

ISSN (print) – 2218-4511 

ISSN (online) – 2227-6718

Registered in the Media Registrants-Register

Identifier in the register: R30-01179 Decision dated August 31, 2023, No. 759

The language of publication is English. 

Issued 4 times a year (March, June, September, December) since 2010

Business Model: Golden Open Access | APC Policy

Editor-in-Chieff             View Editorial Board

Oleksii Lyulyov

Sumy State University | Ukraine

Neuromarketing as a Mechanism of Communication with the Consumer: The Case for Small Business

Olena Chygryn 1,*,  , Kateryna Shevchenko 1, , Oleh Tuliakov 2,  
  1. Department of Marketing, Sumy State University, Ukraine
  2. Department of Psychology, Political Science and Sociocultural Technologies, Sumy State University, Ukraine

     * Corresponding author

Received: 06 December 2023

Revised: 09 May 2024

Accepted: 07 June 2024


Neuromarketing is a modern tool for researching consumer reactions to advertising stimuli and identifying relevant consumer behaviour patterns. Conducting neuromarketing research using eye tracking technology allows us to obtain objective data on consumer perceptions of advertising, websites, product packaging, etc. This article is devoted to studying the structural and content environment of the marketing category and neuromarketing research on advertised materials via the eye-tracking method. The analysis of publishing activity on the topic of neuromarketing carried out with the help of Scopus tools and the VOSviewer toolkit showed a trend of increasing interest from the scientific community in the use of neurotechniques and technologies in the study of consumer behaviour since 2004. The results of the analysis of the structural and content environment have shown the growing interest of scientists in the detailed study of consumer reactions to a product, brand, site, and advertisement, with further conclusions regarding their preferences and priorities. The work revealed that in the field of neuromarketing, there are methods that can be conditionally divided into those that register activity in the brain (neurological) and those that register activity outside the brain (biometric). The characteristics of these methods make it possible to choose the most appropriate method of eye tracking for evaluating consumers’ reactions to advertising posters. Pupil Labs Invisible mobile eyetracker was used as the main tool for neuromarketing research. According to the results of the two stages of the experiment, heatmaps were obtained, which are described by the key metrics of the study: fixations and points of view, heatmaps, areas of interest, and time spent. With the help of research, the most profitable designs of advertising posters for consumers were determined. The influence of different colors and their combinations on the brain activity of potential consumers was analysed. As a result, a conclusion was made regarding the optimal placement of such key elements on the poster as the logo, and the price, the colour range of the presented materials and the fonts that were used were determined. The application of the obtained results of marketing research made it possible to obtain information about how consumers perceive visual stimuli, which, in the future, will be the basis for perfecting marketing communication strategies with the target audience of consumers.

Keywords: neuromarketing; consumers; eye tracking; heatmap; consumer behavior.

How to Cite: Chygryn, O., Sevchenko, K., & Tuliakov, O. (2024). Neuromarketing as a Mechanism of Communication with the Consumer: Case for Small Business. Marketing and Management of Innovations, 15(2), 26–38.

Abstract Views

PDF Downloads


  1. 10 Most Used Eye Tracking Metrics and Terms. iMotions.[Link]
  2. Akan, S., & Atalik, O. (2024). The Impact of Flight Attendants’ Attractiveness on Perceived Service Quality: An EEG Perspective. Marketing and Management of Innovations15(1), 178-194. [Google Scholar][CrossRef]
  3. Aldayel, M., Ykhlef, M., Al-Nafjan, A. (2020). Deep Learning for EEG-Based Preference Classification in Neuromarketing. Applied Sciences. 10(4), 1525. [Google Scholar] [CrossRef]
  4. Alsharif, A. H., Salleh, N. Z. M., Abdullah, M., Khraiwish, A., & Ashaari, A. (2023). Neuromarketing tools used in the marketing mix: A systematic literature and future research agenda. Sage Open13(1), 21582440231156563. [Google Scholar] [CrossRef]
  5. Alsharif, A. H., Salleh, N. Z. M., Al-Zahrani, S. A., & Khraiwish, A. (2022). Consumer behaviour to be considered in advertising: A systematic analysis and future agenda. Behavioral Sciences12(12), 472. [Google Scholar] [CrossRef]
  6. Behavioural Lab (2024). [Link]
  7. Biswas, A., Mashrur, F. R., Rahman, K. M., Miya, M. T. I., Sarker, F., & Mamun, K. A. (2022, March). An overview of neuromarketing research in developing countries: Prospects and challenges. In Proceedings of the 2nd International Conference on Computing Advancements(pp. 149-155). [Google Scholar] [CrossRef]
  8. Brdar, I. (2023). Mind Over Palate: Unveiling the Role of Neuromarketing in the Food Industry. Scientific journal” Meat Technology”64(1), 50-60. [Google Scholar] [CrossRef]
  9. Cardoso, L., Araújo, A., Silva, R., de Almeida, G. G. F., Campos, F., & Santos, L. L. (2024). Demystifying neurotourism: An interdisciplinary approach and research agenda. European Journal of Tourism Research36, 3618-3618. [Google Scholar] [CrossRef]
  10. Cardoso, L., Chen, M. M., Araújo, A., de Almeida, G. G. F., Dias, F., & Moutinho, L. (2022). Accessing neuromarketing scientific performance: Research gaps and emerging topics. Behavioral Sciences12(2), 55. [Google Scholar] [CrossRef]
  11. Chen, T., Lin, Z., Ren, K., & Ren, T. (2023). Neuromarketing research and EEG signal analysis. In International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022)(Vol. 12604, pp. 959-967). SPIE. [Google Scholar] [CrossRef]
  12. Clayton, S., & Karazsia, B. T. (2020). Development and validation of a measure of climate change anxiety. Journal of environmental psychology69, 101434. [Google Scholar] [CrossRef]
  13. de Matos, C. M. (2024). An Investigation Into Sound and Music in Branding: Premises and Practices of Production. In Building Strong Brands and Engaging Customers With Sound(pp. 99-124). IGI Global. [Google Scholar] [CrossRef]
  14. Duque-Hurtado, P., Samboni-Rodriguez, V., Castro-Garcia, M., Montoya-Restrepo, L. A., & Montoya-Restrepo, I. A. (2020). Neuromarketing: Its current status and research perspectives. Estudios gerenciales36(157), 525-539. [Google Scholar] [CrossRef
  15. Gerst, M. D., Kenney, M. A., & Feygina, I. (2021). Improving the usability of climate indicator visualizations through diagnostic design principles. Climatic Change166(3), 33. [Google Scholar] [CrossRef]
  16. Gill, R., & Singh, J. (2022). A Proposed LSTM‐Based Neuromarketing Model for Consumer Emotional State Evaluation Using EEG. Advanced Analytics and Deep Learning Models, 181-206. [Google Scholar] [CrossRef]
  17. Girişken, A. Ç. (2020). Neuromarketing Insights for Start-Up Companies. In Analysing the Strategic Role of Neuromarketing and Consumer Neuroscience(pp. 168-184). IGI Global. [Google Scholar] [CrossRef]
  18. Gunawan, C. N., Chen, Y. J., & Hsu, L. (2023). How online travel agencies’ logo design promotes purchase intention: a behavioral and neuroscientific interpretation of consumers’ construal level. Asia Pacific Journal of Tourism Research28(1), 19-35. [Google Scholar][CrossRef]
  19. Invisible – Home – Pupil Labs Docs.Pupil Labs Docs.[Link]
  20. Kim, J. Y., & Kim, M. J. (2024). Identifying customer preferences through the eye-tracking in travel websites focusing on neuromarketing. Journal of Asian Architecture and Building Engineering23(2), 515-527. [Google Scholar] [CrossRef]
  21. Kotler, S., Mannino, M., Kelso, S., & Huskey, R. (2022). First few seconds for flow: A comprehensive proposal of the neurobiology and neurodynamics of state onset. Neuroscience & Biobehavioral Reviews143, 104956. [Google Scholar] [CrossRef]
  22. Lee, C. K. M., Au, M. Y., & Keung, K. L. (2023, December). EEG-based Online Purchase Decisions and Preferences in Neuromarketing Considering Eco-design. In 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)(pp. 1748-1752). IEEE. [Google Scholar] [CrossRef]
  23. Leung, C. H., & Pang, E. (2021). Improved Electroencephalogram Measurement for Neuromarketing Research. International Journal of Technology, Knowledge and Society17(1), 33. [Google Scholar] [CrossRef]
  24. Levallois, C., Smidts, A., & Wouters, P. (2021). The emergence of neuromarketing investigated through online public communications (2002–2008). Business History63(3), 443-466. [Google Scholar] [CrossRef]
  25. Li, X., Luh, D. B., & Chen, Z. (2024). A Systematic Review and Meta-Analysis of Eye-Tracking Studies for Consumers’ Visual Attention in Online Shopping. Information Technology and Control53(1), 187-205. [Google Scholar] [CrossRef]
  26. Liao, W., Zhang, Y., & Peng, X. (2019). Neurophysiological effect of exposure to gossip on product endorsement and willingness-to-pay. Neuropsychologia132, 107123. [Google Scholar] [CrossRef]
  27. Louro, F. G., & Barboza, R. A. (2024). Neuromarketing: exploring the unconscious side of consumption. Brazilian Journal of Marketing. 23, 252-275. [Google Scholar] [CrossRef]
  28. Lyu, D., Mañas-Viniegra, L. (2023). Tendencias emergentes en neuromarketing: análisis bibliométrico con CiteSpace (2017- 2021). comunicación, 13(2), 75-95. [Google Scholar] [CrossRef]
  29. Ma, Y., Jin, J., Yu, W., Zhang, W., Xu, Z., & Ma, Q. (2018). How is the neural response to the design of experience goods related to personalized preference? An implicit view. Frontiers in Neuroscience12, 760. [Google Scholar] [CrossRef]
  30. Mashrur, F. R., Rahman, K. M., Miya, M. T. I., Vaidyanathan, R., Anwar, S. F., Sarker, F., & Mamun, K. A. (2024). Intelligent neuromarketing framework for consumers’ preference prediction from electroencephalography signals and eye tracking. Journal of Consumer Behaviour23(3), 1146-1157. [Google Scholar][CrossRef]
  31. Meyerding, S. G., & Mehlhose, C. M. (2020). Can neuromarketing add value to the traditional marketing research? An exemplary experiment with functional near-infrared spectroscopy (fNIRS). Journal of Business Research107, 172-185. [Google Scholar] [CrossRef].
  32. Millagala, K., & Gunasinghe, N. (2024). Neuromarketing as a Digital Marketing Strategy to Unravel the Evolution of Marketing Communication. In Applying Business Intelligence and Innovation to Entrepreneurship(pp. 81-105). IGI Global. [Google Scholar] [CrossRef]
  33. Núñez-Cansado, M., Méndez, G. C., & Juárez-Varón, D. (2024). Analysis of the residual effect using neuromarketing technology in audiovisual content entrepreneurship. Sustainable Technology and Entrepreneurship3(3), 100069. [Google Scholar] [CrossRef]
  34. Oberoi, S., Kansra, P., & Awasthi, V. (2024). A Bibliometric Analysis on Research Trends in Neuromarketing: Current Status and Future Directions. Digital Influence on Consumer Habits: Marketing Challenges and Opportunities, 79-92. [Google Scholar] [CrossRef]
  35. Oklander, M., Yashkina, O., Zlatova, I., Cicekli, I., & Letunovska, N. Y. (2024). Digital Marketing in the Survival and Growth Strategies of Small and Medium-Sized Businesses During the War in Ukraine. [Google Scholar]  [CrossRef]
  36. Oliveira, P. M., Guerreiro, J., & Rita, P. (2022). Neuroscience research in consumer behavior: A review and future research agenda. International Journal of Consumer Studies46(5), 2041-2067. [Google Scholar] [CrossRef]
  37. Ouzir, M., Lamrani, H. C., Bradley, R. L., & El Moudden, I. (2024). Neuromarketing and decision-making: Classification of consumer preferences based on changes analysis in the EEG signal of brain regions. Biomedical Signal Processing and Control87, 105469. [Google Scholar] [CrossRef].
  38. Ozkara, B. Y., & Bagozzi, R. (2021). The use of event related potentials brain methods in the study of conscious and unconscious consumer decision making processes. Journal of Retailing and Consumer Services58, 102202. [Google Scholar] [CrossRef]
  39. Panteli, A., Kalaitzi, E., Fidas, C.A. (2024). A review on the use of eeg for the investigation of the factors that affect Consumer’s behavior. Physiology & Behavior. 278, 114509. [Google Scholar] [CrossRef]
  40. Parkhomenko, N., Starchon, P., Vilcekova, L., & Olsavsky, F. (2024).Digitalization of Marketing as an Innovation Tool for Customers’ Evaluation. Marketing and Management of Innovations15(1), 120-130. [Google Scholar][CrossRef]
  41. Pérez, M.Q., Martínez, E.T., López Bernal, S. L., Prat, E.H., Del Campo, L. M., Maimó, L.F., Celdrán, A.H. (2024). Data fusion in neuromarketing: Multimodal analysis of biosignals, lifecycle stages, current advances, datasets, trends, and challenges. Information Fusion, 105, 102231. [Google Scholar] [CrossRef]
  42. Ramos-Galarza, C., & Bolaños-Pasquel, M. (2022, December). Why Do We Buy Things that We Don’t Need: Reflections from Neuropsychology. In International Conference on Marketing and Technologies(pp. 431-438). Singapore: Springer Nature Singapore. [Google Scholar] [CrossRef]
  43. Romero-Luis, J., Carbonell-Alcocer, A., Levratto, V., Gertrudix, M., Casado, M. D. C. G., & Hernandez-Remedios, A. (2023). Design and assessment of an experimental model for evaluating the effectiveness of audiovisual products on the circular economy aimed at promoting environmental awareness. Journal of Cleaner Production423, 138820. [Google Scholar] [CrossRef].
  44. Sakas, D. P., Reklitis, D. P., & Trivellas, P. (2021, December). Digital Marketing Strategy for Competitive Advantage Acquisition Through Neuromarketing in the Logistics Sector. In International Conference on Business Intelligence & Modelling(pp. 95-102). Cham: Springer International Publishing. [Google Scholar] [CrossRef]
  45. Santoso, S. (2024). Consumer Behaviour: Impact of Social and Environmental Sustainability. Marketing and Management of Innovations15(1), 229-240. [Google Scholar][CrossRef]
  46. Singh, P., Alhassan, I., & Khoshaim, L. (2023). What Do You Need to Know? A Systematic Review and Research Agenda on Neuromarketing Discipline. Journal of Theoretical and Applied Electronic Commerce Research18(4), 2007-2032. [Google Scholar] [CrossRef]
  47. Šola, H. M., Qureshi, F. H., & Khawaja, S. (2024). Exploring the Untapped Potential of Neuromarketing in Online Learning: Implications and Challenges for the Higher Education Sector in Europe. Behavioral Sciences14(2), 80. [Google Scholar] [CrossRef]
  48. Tyagi, S., Tyagi, M., Srivastava, A. K., & Saluja, S. (2024). Neuroscience Marketing: A New Age Marketing. In Building Organizational Resilience With Neuroleadership(pp. 215-229). IGI Global. [Google Scholar] [CrossRef]
  49. Wąsikowska, B. (2014). The Application of Eye Tracking in Business. Zeszyty Naukowe Uniwersytetu Szczecińskiego. Wydział Nauk Ekonomicznych i Zarządzania. [Google Scholar]
  50. Yüksel, D. (2023). Investigation of Web-Based Eye-Tracking System Performance under Different Lighting Conditions for Neuromarketing. Journal of Theoretical and Applied Electronic Commerce Research18(4), 2092-2106. [Google Scholar] [CrossRef]
  51. Zhu, Z., Jin, Y., Su, Y., Jia, K., Lin, C. L., & Liu, X. (2022). Bibliometric-based evaluation of the Neuromarketing Research Trend: 2010–2021. Frontiers in psychology13, 872468. [Google Scholar] [CrossRef]

View articles in other formats



Copyright (c) 2024 The Author(s).

Published by Sumy State University