Estimating the Value of Offsite Tracking Data to Advertisers: Evidence from Meta

Third-party cookies and related ‘offsite’ tracking technologies are frequently used to share user data across applications in support of ad delivery. These data are viewed as highly valuable for online advertisers, but their usage faces increasing headwinds. In this paper, we quantify the benefit to advertisers from using such offsite tracking data in their ad delivery. With this goal in mind, we conduct a large-scale, randomized experiment that includes more than 70,000 advertisers on Facebook and Instagram. We first estimate advertising effectiveness at baseline across our broad sample. We then estimate the change in effectiveness of the same campaigns were advertisers to lose the ability to optimize ad delivery with offsite data. In each of these cases, we use recently developed deconvolution techniques to flexibly estimate the underlying distribution of effects. We find a median cost per incremental customer at baseline of $38.16 that under the median loss in effectiveness would rise to $49.93, a 31% increase. Further, we find ads targeted using offsite data generate more long-term customers per dollar than those without, and losing offsite data disproportionately hurts small scale advertisers. Taken together, our results suggest that offsite data bring large benefits to a wide range of advertisers.