Thales S. Teixeira

Emotion-Induced Engagement in Internet Video Advertisements

This study shows how advertisers can leverage emotion and attention to engage consumers in watching Internet video advertisements. In a controlled experiment, the authors assessed joy and surprise through automated facial expression detection for a sample of advertisements. They assessed concentration of attention through eye tracking and viewer retention by recording zapping behavior. This allows tests of predictions about the interplay of these emotions and interperson attention differences at each point in time during exposure. Surprise and joy effectively concentrate attention and retain viewers. However, importantly, the level rather than the velocity of surprise affects attention concentration most, whereas the velocity rather than the level of joy affects viewer retention most. The effect of joy is asymmetric, with higher gains for increases than losses for decreases. Using these findings, the authors develop representative emotion trajectories to support ad design and testing.

Video Content Marketing: The Making of Clips

Consumers have an increasingly wide variety of options available to entertain themselves. This poses a challenge for content aggregators who want to effectively promote their video content online through original trailers of movies, sitcoms, and video games. Marketers are now trying to produce much shorter video clips to promote their content on a variety of digital channels. This research is the first to propose an approach to produce such clips and to study their effectiveness, focusing on comedy movies as an application. Web-based facial-expression tracking is used to study viewers’ real-time emotional responses when watching comedy movie trailers online. These data are used to predict both viewers’ intentions to watch the movie and the movies box office success. The authors then propose an optimization procedure for cutting scenes from trailers to produce clips and test it in an online experiment and in a field experiment. The results provide evidence that the production of short clips using the proposed methodology can be an effective tool to market movies and other online content.

To Zap or Not to Zap: How to Insert the Brand in TV Commercials to Minimize Avoidance

Abstract Vast sums of money are still spent on TV advertising. In an environment of rising perviewer rates for advertisers and increased skipping past ads by consumers it is necessary for advertising managers to understand the determinants of commercial avoidance. In order to optimize brand exposure they need information on how to best retain consumers’ attention from moment-to-moment during television advertising. This large-scale eye tracking study shows that the decision to zap or not to zap depends on how the brand is presented within the commercial. First, the ability of a commercial to concentrate consumers’ visual attention reduced avoidance significantly. Second, the likelihood that viewers will zap can be decreased with a “pulsing strategy” in which brand images are shown more frequently for a shorter period of time within the commercial instead of longer at the beginning or end.

Computational Creative Advertisements.

Making successful video advertisements has long been considered a combination of art and business acumen. In this work, we propose a system to assist human designers to produce more effective advertisements with predictable outcomes. We formalize this concept with a dynamic Bayesian network (DBN), where we represent the knowledge base with data collected from large-scale field experiments in a novel setting. Face and eye tracking which continuously measures viewers emotional responses and viewing interest on 169 television advertisements for 2334 participants, along with moment-to-moment branding activities in the advertisements are used to estimate the model. The resulting DBN represents relationships across advertisement content, viewers emotional responses, as well as effectiveness metrics such as ad avoidance, sharing and influence on purchase. Conditioned on the specified requirement on the ad, a human designer can draw high scoring samples from the DBN, which represent the optimized sequences of branding activities and entertainment content.