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GfK Marketing Intelligence Review

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1865-5866
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Writ Large on Your Face: Observing Emotions Using Automatic Facial Analysis

Dr. Anja Dieckmann / Dr. Matthias Unfried
Published Online: 2014-07-10 | DOI: https://doi.org/10.2478/gfkmir-2014-0009

Abstract

Emotions affect all of our daily decisions and, of course, they also influence our evaluations of brands, products and advertisements. But what exactly do consumers feel when they watch a TV commercial, visit a website or when they interact with a brand in different ways? Measuring such emotions is not an easy task. In the past, the effectiveness of marketing material was evaluated mostly by subsequent surveys. Now, with the emergence of neuroscientific approaches like EEG, the measurement of real-time reactions is possible, for instance, when watching a commercial. However, most neuroscientific procedures are fairly invasive and irritating. For an EEG, for instance, numerous electrodes need to be placed on the participant's scalp. Furthermore, data analysis is highly complex. Scientific expertise is necessary for interpretation, so the procedure remains a black box to most practitioners and the results are still rather controversial. By contrast, automatic facial analysis provides similar information without having to wire study participants. In addition, the results of such analyses are intuitive and easy to interpret even for laypeople. These convincing advantages led GfK Company to decide on facial analysis and to develop a tool suitable for measuring emotional responses to marketing stimuli, making it easily applicable in marketing research practice.

Keywords : Measurement of Emotions; Automatic Facial Analysis; EMO Scan

References

  • Ekman, P. and Friesen, W. (1978): Facial Action Coding System: A Technique for the Measurement of Facial Movement. Palo Alto: Consulting Psychologists Press.Google Scholar

  • Scherer, K. (2005): “What Are Emotions? And How Can They Be Measured?” Social Science Information, Vol. 44, No. 4, pp. 695 - 729.Google Scholar

  • Garbas, J.-U.; Ruf, T.; Unfried, M. and Dieckmann, A. (2013): Towards Robust Real-time Valence Recognition from Facial Expressions for Market Research Applications. Proceedings of the 5th International Conference on Affective Computing and Intelligent Interaction, pp. 570 - 575.Google Scholar

About the article

Published Online: 2014-07-10

Published in Print: 2014-05-01


Citation Information: GfK Marketing Intelligence Review, Volume 6, Issue 1, Pages 52–58, ISSN (Online) 1865-5866, DOI: https://doi.org/10.2478/gfkmir-2014-0009.

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© 2014. This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. BY-NC-ND 3.0

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