Online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on Yahoo!

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Beyond Binary Labels: Political Ideology Prediction of Twitter Users (2017, background): “All of these types of users are very important for researchers aiming to understand group preferences, traits or moral values (Lewis and Reiley, 2014; Hersh, 2015).”
Big Data and Data Science Methods for Management Research (2016, background): “For example, to protect the privacy of customers, Lewis and Reiley (2014) use a third party to match online browsing and offline purchase data.”
The Unfavorable Economics of Measuring the Returns to Advertising (2015, background): “Suppose a targeted individual has a 10%age points higher baseline purchase probability (a realistic degree of targeting similar in magnitude to Lewis and Reiley 2014), then the selection effect is expected to be 30 times larger than the causal effect of the ad.”