33 Pages Posted: 16 Jul 2018 Last revised: 14 Jun 2019

Date Written: May 16, 2019

Abstract

Data brokers often use online browsing records to create digital consumer profiles they sell to marketers as pre-defined audiences for ad targeting. However, this process is a `black box': Little is known about the reliability of the digital profiles that are created, or of the audience identification provided by buying platforms. In this paper, we investigate using three field tests the accuracy of a variety of demographic and audience-interest segments. We examine the accuracy of over 90 third-party audiences across 19 data brokers.



Audience segments vary greatly in quality and are often inaccurate across leading data brokers. In comparison to random audience selection, the use of black-box data profiles on average increased identification of a user with a desired attribute by 0-77%. Audience identification can be improved on average by 123% when combined with optimization software. However, given the high extra costs of targeting solutions and the relative inaccuracy, we find that third-party audiences are often economically unattractive, except for higher-priced media placements.

