Modeling play depth for online video advertising

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Publication Type honors thesis
School or College David Eccles School of Business
Department Marketing
Thesis Supervisor Stephen J. Carson
Honors Advisor/Mentor Ian Skurnik
Creator Coopa, Erik
Title Modeling play depth for online video advertising
Date 2016
Description Internet advertising will reach $260.4 billion by 2020 and "in 2016 global Internet advertising revenue will surpass TV advertising" (PWC, 2015-2016). Internet advertising is a useful medium as it provides plentiful metrics to analyze an advertisement's performance. A relatively new form of online advertising is the use of video advertising. A unique metric for video advertising is play depth-how long viewers watch the advertisement. With this vast amount of money being spent on advertising, it is critical to understand the metrics, especially attribution of clicks and conversions. A problem in the advertising industry is incorrect attribution for success metrics like clicks and conversions. By better understanding how viewers interact with video advertisements, advertisers and platforms can be more effective. Improved advertisements may increase the success of the message and improve the viewers' experiences. Little to no research has been done on modeling video play depth-determining what factors influence video play depth and then what video play depth impacts. A dataset with one-year worth of data was used to model the direct and carryover effects of video play depth. A fixed effect panel data statistical regression was implemented to create an equal analysis among individual advertisements, demographics, and platforms. Results found two significant models. The first model determined that increasing current impressions-or decreasing targeting-led to lower current play depth and that increasing past play depth would lead to greater current play depth. The second model, a less convincing model that needs additional research to ensure certainty, determined that increasing past and current play depth led to less current clicks.
Type Text
Publisher University of Utah
Language eng
Rights Management (c) Erik Coppa
Format Medium application/pdf
ARK ark:/87278/s6xt1k5t
Setname ir_htca
ID 1599612
Reference URL https://collections.lib.utah.edu/ark:/87278/s6xt1k5t
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