Robustness of electroencephalography in marketing research
A meta-analysis
DOI:
https://doi.org/10.12712/rpca.v.202.71055Resumo
This study assesses whether EEG findings in consumer research provide sufficiently consistent cumulative evidence to inform marketing research and decision-making. Using a PRISMA-guided meta-analysis of 18 experimental studies, we estimated the overall effect of EEG markers and examined heterogeneity, moderators, and publication bias under a random-effects model. Results indicate a positive and significant overall effect (d = 0.63), with moderate heterogeneity and stable estimates after sensitivity analyses. The findings suggest that EEG offers complementary value to marketing research by capturing implicit cognitive and affective responses, particularly in pretests involving advertising, brands, products, and price cues.
Downloads
Referências
Adalarasu, K., Ghousiya Begum, K., Vishnu Priyan, M., Devendranath, C., & Sriram, G. V. (2025). Neuro-signaling techniques in advertisement endorsements: Unveiling consumer responses and behavioral trends. Journal of Retailing and Consumer Services, 84(104175), 104175. https://doi.org/10.1016/j.jretconser.2024.104175
Alsharif, A. H., & Isa, S. M. (2025). Electroencephalography studies on marketing stimuli: A literature review and future research agenda. International Journal of Consumer Studies, 49(1). https://doi.org/10.1111/ijcs.70015
Alvino, L., Constantinides, E., & van der Lubbe, R. H. J. (2021). Consumer neuroscience: Attentional preferences for wine labeling reflected in the posterior contralateral negativity. Frontiers in Psychology, 12, 688713. https://doi.org/10.3389/fpsyg.2021.688713
Ausin-Azofra, J. M., Bigne, E., Ruiz, C., Marín-Morales, J., Guixeres, J., & Alcañiz, M. (2021). Do you see what I see? Effectiveness of 360-degree vs. 2D video ads using a neuroscience approach. Frontiers in Psychology, 12, 612717. https://doi.org/10.3389/fpsyg.2021.612717
Baldo, D., Parikh, H., Piu, Y., & Müller, K.-M. (2015). Brain waves predict success of new fashion products: A practical application for the footwear retailing industry. Journal of Creating Value, 1(1), 61–71. https://doi.org/10.1177/2394964315569625
Barker, T. H., Habibi, N., Aromataris, E., Stone, J. C., Leonardi-Bee, J., Sears, K., Hasanoff, S., Klugar, M., Tufanaru, C., Moola, S., & Munn, Z. (2024). The revised JBI critical appraisal tool for the assessment of risk of bias for quasi-experimental studies. JBI Evidence Synthesis, 22(3), 378–388. https://doi.org/10.11124/JBIES-23-00268
Boksem, M. A. S., & Smidts, A. (2015). Brain responses to movie trailers predict individual preferences for movies and their population-wide commercial success. JMR, Journal of Marketing Research, 52(4), 482–492. https://doi.org/10.1509/jmr.13.0572
Bosshard, S. S., Bourke, J. D., Kunaharan, S., Koller, M., & Walla, P. (2016). Established liked versus disliked brands: Brain activity, implicit associations and explicit responses. Cogent Psychology, 3(1), 1176691. https://doi.org/10.1080/23311908.2016.1176691
Byrne, A., Bonfiglio, E., Rigby, C., & Edelstyn, N. (2022). A systematic review of the prediction of consumer preference using EEG measures and machine-learning in neuromarketing research. Brain Informatics, 9(1), 27. https://doi.org/10.1186/s40708-022-00175-3
Cartocci, G., Caratù, M., Modica, E., Maglione, A. G., Rossi, D., Cherubino, P., & Babiloni, F. (2017). Electroencephalographic, Heart Rate, and Galvanic Skin Response assessment for an advertising perception study: Application to antismoking public service announcements. Journal of Visualized Experiments: JoVE, 126. https://doi.org/10.3791/55872
Daugherty T, Hoffman E, Kennedy K, Nolan M. (2018). Measuring consumer neural activation to differentiate cognitive processing of advertising: Revisiting Krugman. European Journal of Marketing, 52(1–2), 182–198. https://doi.org/10.1108/EJM-10-2017-0657
Fudali-Czyż, A., Ratomska, M., Cudo, A., Francuz, P., Kopiś, N., & Tużnik, P. (2016). Controlled categorisation processing in brand extension evaluation by Indo-European language speakers. An ERP study. Neuroscience Letters, 628, 30–34. https://doi.org/10.1016/j.neulet.2016.06.005
Fugate, D. L. (2007). Neuromarketing: a layman’s look at neuroscience and its potential application to marketing practice. The Journal of Consumer Marketing, 24(7), 385–394. https://doi.org/10.1108/07363760710834807
García-Madariaga, J., Blasco López, M.-F., Burgos, I. M., & Virto, N. R. (2019). Do isolated packaging variables influence consumers’ attention and preferences? Physiology & Behavior, 200, 96–103. https://doi.org/10.1016/j.physbeh.2018.04.030
Genevsky, A., & Boksem, M. (2024). Applications in Consumer Neuroscience: Decoding and Neuroforecasting. https://doi.org/10.2139/ssrn.5001469
Gerner, N., Pickerle, D., Höller, Y., & Hartl, A. (2025). Neurophysiological markers of design-induced cognitive changes: A feasibility study with consumer-grade mobile EEG. Brain Sciences, 15(5), 432. https://doi.org/10.3390/brainsci15050432
Goto, N., Lim, X. L., Shee, D., Hatano, A., Khong, K. W., Buratto, L. G., Watabe, M., & Schaefer, A. (2019). Can brain waves really tell if a product will be purchased? Inferring consumer preferences from single-item brain potentials. Frontiers in Integrative Neuroscience, 13, 19. https://doi.org/10.3389/fnint.2019.00019
Gountas, J., Gountas, S., Ciorciari, J., & Sharma, P. (2019). Looking beyond traditional measures of advertising impact: Using neuroscientific methods to evaluate social marketing messages. Journal of Business Research, 105, 121–135. https://doi.org/10.1016/j.jbusres.2019.07.011
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 Research, 28(1), 19–35. https://doi.org/10.1080/10941665.2023.2187701
Hakim, A., Klorfeld, S., Sela, T., Friedman, D., Shabat-Simon, M., & Levy, D. J. (2021). Machines learn neuromarketing: Improving preference prediction from self-reports using multiple EEG measures and machine learning. International Journal of Research in Marketing, 38(3), 770–791. https://doi.org/10.1016/j.ijresmar.2020.10.005
Hsu, L., & Chen, Y.-J. (2020). Neuromarketing, subliminal advertising, and hotel selection: An EEG study. Australasian Marketing Journal (AMJ), 28(4), 200–208. https://doi.org/10.1016/j.ausmj.2020.04.009
Ishtiaque, F., Miya, M. T. I., Mashrur, F. R., Rahman, K. M., Vaidyanathan, R., Anwar, S. F., Sarker, F., Tat, H. H., Hamid, A. B. A., & Mamun, K. A. (2025). Systematic comparison between a research-grade EEG device and a consumer-grade BCI device for predicting consumer preference using an ML framework. Multimedia Tools and Applications, 84(34), 42807–42825. https://doi.org/10.1007/s11042-025-20812-3
Izadi, B., Ghaedi, A., & Ghasemian, M. (2022). Neuropsychological responses of consumers to promotion strategies and the decision to buy sports products. Asia Pacific Journal of Marketing and Logistics, 34(6), 1203–1221. https://doi.org/10.1108/apjml-01-2021-0026
Kalaganis, F. P., Georgiadis, K., Oikonomou, V. P., Laskaris, N. A., Nikolopoulos, S., & Kompatsiaris, I. (2025). A hybrid neuromarketing approach exploiting EEG graph signal processing and gaze dynamic patterning. Brain Informatics, 12(1), 23. https://doi.org/10.1186/s40708-025-00272-z
Khondakar, M. F. K., Sarowar, M. H., Chowdhury, M. H., Majumder, S., Hossain, M. A., Dewan, M. A. A., & Hossain, Q. D. (2024). A systematic review on EEG-based neuromarketing: recent trends and analyzing techniques. Brain Informatics, 11(1), 17. https://doi.org/10.1186/s40708-024-00229-8
Lee, E.-J., Kwon, G., Shin, H. J., Yang, S., Lee, S., & Suh, M. (2014). The spell of green: Can frontal EEG activations identify green consumers? Journal of Business Ethics, 122(3), 511–521. https://doi.org/10.1007/s10551-013-1775-2
Liao, W., Zhang, Y., & Peng, X. (2019). Neurophysiological effect of exposure to gossip on product endorsement and willingness-to-pay. Neuropsychologia, 132(107123), 107123. https://doi.org/10.1016/j.neuropsychologia.2019.107123
Lim, W. M. (2018). Demystifying neuromarketing. Journal of Business Research, 91, 205–220. https://doi.org/10.1016/j.jbusres.2018.05.036
Ma, Q., Feng, Y., Xu, Q., Bian, J., & Tang, H. (2012). Brain potentials associated with the outcome processing in framing effects. Neuroscience Letters, 528(2), 110–113. https://doi.org/10.1016/j.neulet.2012.09.016
Ma, Q., Mao, W., & Hu, L. (2022). Electrophysiological evidence for the effects of pain on the different stages of reward evaluation under a purchasing situation. Frontiers in Psychology, 13, 943699. https://doi.org/10.3389/fpsyg.2022.943699
Ma, Q., Wang, M., He, Y., Tan, Y., & Zhang, L. (2021). Does mobile payment change consumers’ perception during payment process? -An ERP study. Neuroscience Letters, 762(136138), 136138. https://doi.org/10.1016/j.neulet.2021.136138
Matukin, M., Ohme, R., & Boshoff, C. (2016). Toward a better understanding of advertising stimuli processing: Exploring the link between consumers’ eye fixation and their subconscious responses. Journal of Advertising Research, 56(2), 205–216. https://doi.org/10.2501/jar-2016-017
Mengual-Recuerda, A., Tur-Viñes, V., & Juárez-Varón, D. (2020). Neuromarketing in haute cuisine gastronomic experiences. Frontiers in Psychology, 11, 1772. https://doi.org/10.3389/fpsyg.2020.01772
Nittono, H., & Watari, K. (2017). Effects of food sampling on brain potential responses to food branding. Psychologia; an International Journal of Psychology in the Orient, 60(1), 3–15. https://doi.org/10.2117/psysoc.2017.3
Ohme, R., Reykowska, D., Wiener, D., & Choromanska, A. (2010). Application of frontal EEG asymmetry to advertising research. Journal Of Economic Psychology, 31(5), 785–793. https://doi.org/10.1016/j.joep.2010.03.008
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ (Clinical Research Ed.), 372, n71. https://doi.org/10.1136/bmj.n71
Panteli, A., Kalaitzi, E., & Fidas, C. A. (2025). Identifying individual information processing styles during advertisement viewing through EEG-driven classifiers. Information (Basel), 16(9), 757. https://doi.org/10.3390/info16090757
Paul, J., & Barari, M. (2022). Meta‐analysis and traditional systematic literature reviews—What, why, when, where, and how? Psychology & Marketing, 39(6), 1099–1115. https://doi.org/10.1002/mar.21657
Pereira, M. H. N., Melo, F. L. N. B. de, Soares, A. M. J., Ferreira, P. B. S., Silva, M. P. da, & Morya, E. (2024). Eye-Tracking como correlato fisiológico do comportamento do consumidor: uma revisão sistemática da literatura. Revista Brasileira de Marketing, 23(1), 300–365. https://doi.org/10.5585/remark.v23i1.23271
Pozharliev, R., Rossi, D., & De Angelis, M. (2022). Consumers’ self-reported and brain responses to advertising post on Instagram: the effect of number of followers and argument quality. European Journal of Marketing, 56(3), 922–948. https://doi.org/10.1108/ejm-09-2020-0719
Raiesdana, S., & Mousakhani, M. (2022). An EEG-based neuromarketing approach for analyzing the preference of an electric car. Computational Intelligence and Neuroscience, 2022, 9002101. https://doi.org/10.1155/2022/9002101
Ramsøy, T. Z., Skov, M., Christensen, M. K., & Stahlhut, C. (2018). Frontal brain asymmetry and willingness to pay. Frontiers in Neuroscience, 12, 138. https://doi.org/10.3389/fnins.2018.00138
Shang, Q., Chen, J., Ma, H., Wang, C., & Ru, X. (2024). Influence of AI recommendation method and product type on consumers’ acceptance: an event-related potential study. Current Psychology (New Brunswick, N.J.), 43(8), 7535–7546. https://doi.org/10.1007/s12144-023-04948-9
Telpaz, A., Webb, R., & Levy, D. J. (2015). Using EEG to predict consumers’ future choices. JMR, Journal of Marketing Research, 52(4), 511–529. https://doi.org/10.1509/jmr.13.0564
Touchette, B., & Lee, S.-E. (2017). Measuring neural responses to apparel product attractiveness: An application of frontal asymmetry theory. Clothing and Textiles Research Journal, 35(1), 3–15. https://doi.org/10.1177/0887302x16673157
Vecchiato, G., Cherubino, P., Maglione, A. G., Ezquierro, M. T. H., Marinozzi, F., Bini, F., Trettel, A., & Babiloni, F. (2014). How to measure cerebral correlates of emotions in marketing relevant tasks. Cognitive Computation, 6(4), 856–871. https://doi.org/10.1007/s12559-014-9304-x
Vecchiato, G., Maglione, A. G., Cherubino, P., Wasikowska, B., Wawrzyniak, A., Latuszynska, A., Latuszynska, M., Nermend, K., Graziani, I., Leucci, M. R., Trettel, A., & Babiloni, F. (2014). Neurophysiological tools to investigate consumer’s gender differences during the observation of TV commercials. Computational and Mathematical Methods in Medicine, 2014, 912981. https://doi.org/10.1155/2014/912981
Vecchiato, G., Toppi, J., Astolfi, L., De Vico Fallani, F., Cincotti, F., Mattia, D., Bez, F., & Babiloni, F. (2011). Spectral EEG frontal asymmetries correlate with the experienced pleasantness of TV commercial advertisements. Medical & Biological Engineering & Computing, 49(5), 579–583. https://doi.org/10.1007/s11517-011-0747-x
Venkatraman, V., Dimoka, A., Pavlou, P. A., Vo, K., Hampton, W., Bollinger, B., Hershfield, H. E., Ishihara, M., & Winer, R. S. (2015). Predicting advertising success beyond traditional measures: New insights from neurophysiological methods and market response modeling. JMR, Journal of Marketing Research, 52(4), 436–452. https://doi.org/10.1509/jmr.13.0593
Vieira, E. V., Dos Reis, Z. C., Matte, J., Miri, D. H., Chais, C., Ganzer, P. P., & Olea, P. M. (2020). Aplicabilidade Das Técnicas De Neuromarketing Em Empresas De Grande Porte Da Serra Gaúcha. Revista Eletrônica de Estratégia & Negócios, 13(1), 3. https://doi.org/10.19177/reen.v13e120203-26
Vozzi, A., Ronca, V., Aricò, P., Borghini, G., Sciaraffa, N., Cherubino, P., Trettel, A., Babiloni, F., & Di Flumeri, G. (2021). The sample size matters: To what extent the participant reduction affects the outcomes of a neuroscientific research. A case-study in neuromarketing field. Sensors (Basel, Switzerland), 21(18), 6088. https://doi.org/10.3390/s21186088
Wajid, A., Raziq, M. M., Ahmed, Q. M., & Ahmad, M. (2021). Observing viewers’ self-reported and neurophysiological responses to message appeal in social media advertisements. Journal of Retailing and Consumer Services, 59(102373), 102373. https://doi.org/10.1016/j.jretconser.2020.102373
Wang, C., Li, Y., Luo, X., Ma, Q., Fu, W., & Fu, H. (2018). The effects of money on fake rating behavior in E-commerce: Electrophysiological time course evidence from consumers. Frontiers in Neuroscience, 12, 156. https://doi.org/10.3389/fnins.2018.00156
Wang, G., Li, J., Zhu, C., Wang, S., & Jiang, S. (2021). How do reference points influence the representation of the N200 for consumer preference? Frontiers in Psychology, 12, 645775. https://doi.org/10.3389/fpsyg.2021.645775
Wang, J., Alsharif, A. H., Abd Aziz, N., Khraiwish, A., & Salleh, N. Z. M. (2024). Neuro-insights in marketing research: A PRISMA-based analysis of EEG studies on consumer behavior. SAGE Open, 14(4). https://doi.org/10.1177/21582440241305365
Wei, Q., Bao, A., Lv, D., Liu, S., Chen, S., Chi, Y., & Zuo, J. (2024). The influence of message frame and product type on green consumer purchase decisions : an ERPs study. Scientific Reports, 14(1), 23232. https://doi.org/10.1038/s41598-024-75056-2
Xie, J., Wang, R., & Chang, S. (2014). The mechanism of valence-space metaphors: ERP evidence for affective word processing. PloS One, 9(6), e99479. https://doi.org/10.1371/journal.pone.0099479
Zanolie, K., de Cremer, D., Güroğlu, B., & Crone, E. A. (2015). Rejection in bargaining situations: An event-related potential study in adolescents and adults. PloS One, 10(10), e0139953. https://doi.org/10.1371/journal.pone.0139953
Zeng, L., Lin, M., Xiao, K., Wang, J., & Zhou, H. (2021). Like/dislike prediction for sport shoes with electroencephalography: An application of neuromarketing. Frontiers in Human Neuroscience, 15, 793952. https://doi.org/10.3389/fnhum.2021.793952
Zito, M., Fici, A., Bilucaglia, M., Ambrogetti, F. S., & Russo, V. (2021). Assessing the emotional response in social communication: The role of neuromarketing. Frontiers in Psychology, 12, 625570. https://doi.org/10.3389/fpsyg.2021.625570
Downloads
Publicado
Edição
Seção
Licença
Os autores mantêm os direitos autorais e concedem à revista o direito de primeira publicação, com o trabalho simultaneamente licenciado sob a Creative Commons Attribution License, permitindo o compartilhamento do trabalho com reconhecimento da autoria e publicação inicial nesta revista.
A Revista usa o CC BY. Essa licença permite que outras pessoas distribuam, remixem, adaptem e desenvolvam seu trabalho, mesmo comercialmente, desde que sejam creditadas pela criação original. Essa é a licença mais flexível oferecida. Recomendado para máxima disseminação e uso de materiais licenciados.
Os autores têm autorização para assumir contratos adicionais separadamente, para distribuição não-exclusiva da versão do trabalho publicada nesta revista (ex.: publicar em repositório institucional ou como capítulo de livro), sempre com reconhecimento de autoria e publicação inicial nesta revista.
A Revista ulitiliza o DOI (Digital Object Identifier ) desde 2007 O DOI com a finalidade de autenticar cada artigo, portanto seu conteúdo digital.

