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Efficient Measurement of Causal Impact in Digital Advertising Using Online Ad Viewability: Online display ads offer a level of granularity in observable metrics that is impossible to achieve for traditional, non-digital advertisers. However, as advertising budgets comprise an increasing amount of marketing spend, true return on investment (ROI) is increasingly important but often goes unmeasured. An important question to answer is how much incremental revenue was generated by an online campaign. In general, there are two common approaches to measuring the causal impact of a campaign: (1) a randomized experiment and (2) using observational data. The first technique is preferred due to its ability to give an unbiased estimate of a campaign’s effect, but is usually prohibitively costly. The second requires no additional ad spend, but is plagued by complex modeling choices and biases. Using a unique position in the online advertising pipeline to create a “natural experiment”, we propose a novel approach to measuring campaign effectiveness that utilizes detailed measurements of whether ads were actually viewed by a user. Treating users that have never been exposed to a viewable ad as a control group, we are able to mimic the setup of a randomized experiment without any additional cost while avoiding the biases that are typical when using observational data.