Cross-Platform Spillover Effects in Consumption of Viral Content: A Quasi-Experimental Analysis Using Synthetic Controls

Published Online:https://doi.org/10.1287/isre.2019.0897

To inform product release and distribution strategies, research has analyzed cross-market spillovers in new product adoption. However, models that examine these effects for digital and viral media are still evolving. Given resistance to advertising, firms often seek to promote their own viral content to boost brand awareness. However, a key shortcoming of virality is its ephemeral nature. To gain insight into sustaining virality, we develop a quasi-experimental approach that estimates the backward spillover onto a focal platform by introducing a piece of content onto a new platform. We posit that introducing content to the audience of a new platform can generate word of mouth, which may affect its consumption within an earlier platform. We estimate these spillovers using data on 381 viral videos on 26 platforms (e.g., YouTube, Vimeo) and observe how consumption of videos on an initial “lead” platform is affected by their subsequent introduction onto “lag” platforms. This spillover is estimated as follows: for each multiplatform video, we compare its view growth after being introduced onto a new platform to that of a synthetic control based on similar single-platform videos. Analysis of 275 such spillover scenarios reveals that introducing a video onto a lag platform roughly doubles its subsequent view growth in the lead platform. This positive cross-platform spillover is persistent, bursty, and strongest in the first 42 days. We find that spillover is boosted when the video is consumed more in the lag platform, when the consumption rate peaks earlier in the lag platform, and when the lag platform targets a foreign market. Delaying a video’s introduction onto a lag platform affects spillover concavely, whereas its introduction onto additional platforms shows diminishing returns. We find further support for positive spillover through a small-scale randomized field experiment. Implications are discussed for platforms, content creators, and policy makers.

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