Zapping Index:Using Smile to Measure Advertisement Zapping Likelihood

Abstract

In marketing and advertising research, "zapping" is defined as the action when a viewer stops watching a commercial. Researchers analyze users' behavior in order to prevent zapping which helps advertisers to design effective commercials. Since emotions can be used to engage consumers, in this paper, we leverage automated facial expression analysis to understand consumers' zapping behavior. Firstly, we provide an accurate moment-to-moment smile detection algorithm. Secondly, we formulate a binary classification problem (zapping/non-zapping) based on real-world scenarios, and adopt smile response as the feature to predict zapping. Thirdly, to cope with the lack of a metric in advertising evaluation, we propose a new metric called Zapping Index (ZI). ZI is a moment-to-moment measurement of a user's zapping probability. It gauges not only the reaction of a user, but also the preference of a user to commercials. Finally, extensive experiments are performed to provide insights and we make recommendations that will be useful to both advertisers and advertisement publishers.

Automatic facial coding predicts self-report of emotion, advertisement and brand effects elicited by video commercials

“…Accordingly, AFC of smiling intensity correlates with advertisement likeability ( Lewinski et al, 2014b ; McDuff et al, 2014 , 2015 ), brand likeability ( Lewinski et al, 2014b ), and the purchase intentions of advertised brands ( Teixeira et al, 2014 ; McDuff et al, 2015 ). Furthermore, increased smiling was also found to reduce zapping behavior ( Yang et al, 2014 ; Chen et al, 2016 ), decrease attention dispersion ( Teixeira et al, 2012 ), and predict long-term attitude changes ( Hamelin et al, 2017 ). Taken together, there is evidence that AFC of smiling predicts several steps of the advertisement and brand effects proposed by the affect-transfer hypothesis.…”

Emotional Trace: Mapping of Facial Expression to Valence-arousal Space

“…A student engagement, which is considered as an important measure for a contemporary education, can be measured from the faces [4]. Nowadays, it is also used to measure the responses to advertisement [5].…”