手法を比較

	Neuromarketing with EEG	Facial Coding in Advertising Research
分野	マーケティング	マーケティング
系統	Process / pipeline	Process / pipeline
提唱年	2015	1978
提唱者	Hilke Plassmann, Vinod Venkatraman, Scott Huettel & Carolyn Yoon; Richard Davidson (frontal asymmetry)	Paul Ekman & Wallace Friesen (FACS); Daniel McDuff & Rana el Kaliouby (automated ad coding)
種類	Neurophysiological measurement pipeline for consumer response	Facial-expression measurement pipeline for emotional ad response
原典	Plassmann, H., Venkatraman, V., Huettel, S., & Yoon, C. (2015). Consumer Neuroscience: Applications, Challenges, and Possible Solutions. Journal of Marketing Research, 52(4), 427-435.	Ekman, P., & Friesen, W. V. (1978). Facial Action Coding System: A Technique for the Measurement of Facial Movement. Palo Alto, CA: Consulting Psychologists Press. ISBN: 9780931835018
別名	Consumer Neuroscience, EEG Neuromarketing, Neuro-Ad Testing, Brain-Based Advertising Measurement	Facial Expression Analysis, Automated Facial Coding, Emotion AI for Ads, Facial Action Coding for Marketing
関連	3	3
概要	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.	Facial coding measures consumers' emotional responses to advertising by analyzing the movements of their faces while they watch. It rests on Paul Ekman and Wallace Friesen's Facial Action Coding System (FACS), which decomposes any expression into elemental action units, the contractions of individual facial muscles such as the lip-corner pull of a smile or the brow lowering of a frown. Manual FACS coding is precise but slow, so the field has shifted to automated facial coding, in which computer-vision models detect landmarks and action units frame by frame and map them to emotions and to continuous valence and arousal. Daniel McDuff, Rana el Kaliouby, and colleagues showed at scale that these automatically measured facial responses to ads predict ad liking and even changes in purchase intent. Aggregated across viewers, the result is a second-by-second emotional response curve over the ad, revealing where it amuses, surprises, bores, or repels. Facial coding thus turns spontaneous, fleeting expressions into a quantitative, time-resolved index of how an ad makes people feel.