Digital attribution may sound simple in that it involves isolating advertising tactics and assessing their impact on consumer decision making. But without sufficient data at the individual consumer level, advertisers are having trouble building “actionable marketing mix models for accurately measuring marketing ROI,” writes Gian M. Fulgoni.
The Comscore, Inc. cofounder and former CEO points to walled gardens—Amazon, Facebook, and Google, for example—for not openly sharing what they perceive to be proprietary data: vast data banks that can provide valuable insight on consumer behavior and media spending. This “can constrain the efforts of independent research companies to measure the financial return from an investment in advertising on walled gardens’ platforms,” he writes.
Granted, there are issues associated with multiplatform video-content consumption, among them: challenges of analyzing single-source models across a number of different touchpoints, and the nature of data privacy and the potential for overregulation. In the face of all of these hurdles, “analysts can pursue two paths,” he suggests:
“They can run marketing-mix models that exclude the causal components for which data are unavailable, or they can use causal data that’s aggregated across users. Neither approach is optimal.
Will the situation improve? “To a large degree,” Fulgoni concludes, “it depends on the extent to which the various digital-advertising platforms come to see a benefit in sharing their data with third parties.”
Source: Ford, J. (2018, December). What We Know About Digital Attribution. Journal of Advertising Research.
Editor’s Note: Commentary from an industry icon.