Finding the Sweet Spot: Ad Targeting on Streaming Media
75 Pages Posted: 17 Dec 2019 Last revised: 7 Aug 2021
Date Written: August 6, 2021
A majority of US households view on-demand content on streaming video services. Not surprisingly, ad spending on these online services is growing rapidly. However, extant research on streaming media has not explored the balance between the interest of the viewer (content consumption) with that of the platform (ad exposure). We do this using two new metrics that capture the interplay between content consumption and ad exposure using viewing data on a streaming media platform. The first metric (Bingeability) measures non-linear content consumption while the second metric (Ad Tolerance) measures the willingness of a viewer to continue viewing after ad exposure. Using causal machine learning methods that comprise a tree-based model with instrumental variables, we capture the impact of ad delivery on Bingeability and Ad Tolerance for individual viewers for each viewing session. The results indicate that the “sweet spot” that balances the interest of the viewer and the platform consists of short (ad) pod durations that are equally spaced at longer intervals during a viewing session. We discuss the implications of our results for managers of streaming platforms.
Keywords: Advertising, Streaming Media, Binge-Watching, Machine Learning, Causal Inference
JEL Classification: M31, M37, C14, C36, C61
Suggested Citation: Suggested Citation