Abstract:
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We study the impact of TV advertising on viewers' online search behaviors. In particular, we develop methodologies to estimate the incremental searches that can be causally attributed to TV ad spots, based on a Bayesian Structural Time Series (BSTS) model named CausalImpact. Simulation studies show that the TV induced incremental search volumes can be accurately estimated in most cases. We then demonstrate our methods with a case study, and present the insights that can be generated by such analyses.
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