Comparar métodos

	Neuromarketing with EEG	Implicit Reaction-Time Brand Measures
Área	Marketing	Marketing
Família	Process / pipeline	Process / pipeline
Ano de origem	2015	1986
Autor original	Hilke Plassmann, Vinod Venkatraman, Scott Huettel & Carolyn Yoon; Richard Davidson (frontal asymmetry)	Russell Fazio (affective priming); Anthony Greenwald, Brian Nosek & Mahzarin Banaji (D-score scoring)
Tipo	Neurophysiological measurement pipeline for consumer response	Response-latency measurement pipeline for implicit brand associations
Fonte seminal	Plassmann, H., Venkatraman, V., Huettel, S., & Yoon, C. (2015). Consumer Neuroscience: Applications, Challenges, and Possible Solutions. Journal of Marketing Research, 52(4), 427-435.	Fazio, R. H., Sanbonmatsu, D. M., Powell, M. C., & Kardes, F. R. (1986). On the automatic activation of attitudes. Journal of Personality and Social Psychology, 50(2), 229-238.
Outros nomes	Consumer Neuroscience, EEG Neuromarketing, Neuro-Ad Testing, Brain-Based Advertising Measurement	Implicit Brand Association Measures, Response-Latency Brand Testing, Affective Priming for Brands, Implicit Brand Attitude Measurement
Relacionados	3	3
Resumo	Neuromarketing, or consumer neuroscience, applies brain-imaging and biometric measurement to study how consumers respond to advertising, products, brands, and prices. Electroencephalography (EEG) is its most widely used tool because it records electrical activity from scalp electrodes with millisecond resolution, capturing the rapid dynamics of attention and emotion as a stimulus unfolds. From the cleaned signal, researchers derive indices such as frontal alpha asymmetry, which Richard Davidson's work links to approach versus withdrawal motivation, along with engagement ratios from beta, alpha, and theta power and event-related potentials time-locked to stimulus events. These neural measures are often combined with autonomic biometrics such as galvanic skin response and heart rate, and with fMRI in lab settings, to triangulate emotional arousal and valence. Plassmann, Venkatraman, Huettel, and Yoon's 2015 Journal of Marketing Research article set out the legitimate applications and the methodological challenges of this field. The promise is to capture moment-to-moment, non-conscious responses that consumers cannot or will not verbalize, while the discipline insists those signals be interpreted cautiously and validated against behavior.	Implicit reaction-time brand measures use how fast people respond, rather than what they say, to gauge the associations a brand automatically triggers. The logic comes from Russell Fazio's demonstration that strong attitudes are activated automatically: when a brand acts as a prime, it speeds responses to evaluatively congruent targets and slows responses to incongruent ones, and the size of that facilitation indexes the brand's implicit evaluation. Building on this, response-latency tasks pair brands with positive or negative words, with attribute categories, or with competing brands, and read off implicit associations from millisecond differences in reaction time. Anthony Greenwald, Brian Nosek, and Mahzarin Banaji's improved scoring algorithm turns these latency differences into a standardized D-score that is comparable across people and tasks. Because the measures tap associations that operate before deliberate editing, they capture brand equity that consumers may be unwilling or unable to report. The result is a behaviorally grounded, hard-to-fake complement to survey-based brand tracking.