方法对比

	Eye-Tracking in Advertising Research	Facial Coding in Advertising Research
领域	市场营销	市场营销
方法族	Process / pipeline	Process / pipeline
起源年份	2008	1978
提出者	Michel Wedel & Rik Pieters	Paul Ekman & Wallace Friesen (FACS); Daniel McDuff & Rana el Kaliouby (automated ad coding)
类型	Attention-measurement pipeline for visual marketing stimuli	Facial-expression measurement pipeline for emotional ad response
开创性文献	Wedel, M., & Pieters, R. (2008). Eye Tracking for Visual Marketing. Foundations and Trends in Marketing, 1(4), 231-320.	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
别名	Visual Attention Tracking, Gaze Tracking for Marketing, Oculometry in Advertising, Eye-Movement Analysis of Ads	Facial Expression Analysis, Automated Facial Coding, Emotion AI for Ads, Facial Action Coding for Marketing
相关	3	3
摘要	Eye-tracking in advertising and packaging research measures where, when, and for how long consumers look at marketing stimuli, turning raw gaze into an objective record of visual attention. A camera-based eye-tracker samples the point of regard many times per second, and the resulting stream is parsed into fixations (relatively stable gazes during which information is taken in) and saccades (rapid jumps between them). Researchers overlay areas of interest such as the brand logo, headline, pack-shot, or call-to-action, and compute metrics including dwell time, time-to-first-fixation, and refixation counts for each region. Michel Wedel and Rik Pieters's 2008 monograph Eye Tracking for Visual Marketing consolidated the theory of visual attention behind these measures and showed how attention to ad and package elements relates to memory, brand evaluation, and choice. Aggregated across respondents, the data yield heatmaps and gaze sequences that designers use to diagnose whether the right elements capture attention in the right order. The method bridges low-level perception and high-level marketing outcomes by treating attention as a measurable, manipulable mediator of advertising effectiveness.	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.