Understanding virality of YouTube video ads: dynamics, drivers, and effects

Recent years have seen a proliferation of branded video ads on YouTube. Brands are increasingly willing to bypass traditional mass media and place ads on YouTube. If the video ad goes viral, it creates huge short-term brand exposure. However, creating viral videos is difficult. Most video ads are duds. This is because on YouTube, consumers decide what to watch, whether to share, and whether to subscribe to the brand channel. These unique features call for a careful analysis of YouTube video ads to help brands better design and place their ads on YouTube. ❧ We scrape hourly data from YouTube for a large number of branded video ads. Our collected data include various measures of consumers' social engagement (views, shares, likes/dislikes, comments). We also collect channel subscriptions and abnormal stock returns to gauge the effect of advertising. ❧ We examine the virality of video ads from three aspects. First, we study the process that a video ad spreads. We construct a dynamic system that jointly models the process of product adoption and share generation. We also model the dynamic interrelationship between adoption and sharing resulting from the change of consumers' adoption and sharing behavior over time. The empirical inference of the model sheds light on the patterns of adoptions and shares, characteristics of viral diffusion, intra-day seasonality, economic values of social shares, and dynamics of share effectiveness and sharing propensity. These results provide insights on the strategy of ad promotion, share stimulation, and ad seeding. ❧ Second, we analyze the drivers of viral video ads. We develop an instrument to rate the content of a large number of ads on over 30 executional cues drawn from the behavioral literature on advertising. These cues cover argument, emotion, endorsement, surprise, humor, branding, ad length, sex and many other variables. We analyze social shares as a function of the executional cues and identify the important drivers of virality. Our empirical findings provide important implications for the current practice of advertising via video ads. ❧ Third, we investigate the effects of video ads on channel subscriptions and abnormal stock returns of the brand. We build a dynamic model that links the views of video ads to the channel subscriptions of the brand. We quantify the effect of a view on channel subscription, identify the effective ads, test the effectiveness of viral ads compared to non-viral ads, compare different appealing methods used in ads and access the effects of video ads on abnormal stock returns.