AI

A Method for Measuring Online Audiences

Abstract

We present a method for measuring the reach and frequency of online ad campaigns by audience attributes. This method uses a combination of data sources, including ad server logs, publisher provided user data (PPD), census data, and a representative online panel. It adjusts for known problems with cookie data and potential non-representative and inaccurate PPD. It generalizes for multiple publishers and for targeting based on the PPD. The method includes the conversion of adjusted cookie counts to unique audience counts. The benefit of our method is that we get both reduced variance from server logs and reduced bias from the panel. Simulation results and a case study are presented.