Estimating the Value of Offsite Data to Advertisers on Meta
We study the extent to which advertisers benefit from data that are shared across applications. These types of data are viewed as highly valuable for digital advertisers today. However, product changes and privacy regulations threaten the ability of advertisers to use such data. We evaluate one of the most common ways advertisers use offsite data by running a large-scale study with a hundred thousand advertisers on Meta. Within campaigns, we experimentally estimate both the effectiveness of advertising under business as usual, which uses offsite data, as well as how that would change under a loss of offsite data. Using deconvolution techniques, we flexibly estimate the underlying distribution of treatment effects across our sample. We find a median cost per incremental customer using business as usual targeting techniques of $43.88. Without access to offsite data, the median cost per incremental customer would rise to $60.19, a 37% increase. Similarly, analyzing purchasing behavior six months after our experiment, ads delivered with offsite data generate substantially more long-term customers per dollar, with a comparable delta in costs. Further, we find evidence that small scale advertisers and those in CPG, Retail, and E-commerce are especially affected. Taken together, our results suggest a substantial benefit of offsite data across a wide range of advertisers, an important input into policy in this space.
Nils Wernerfelt, Anna Tuchman, Bradley Shapiro, Robert Moakler
Wernerfelt, Nils, Anna Tuchman, Bradley Shapiro, and Robert Moakler. 2022. Estimating the Value of Offsite Data to Advertisers on Meta.LINK