Virtual People: Actionable Reach Modeling

Jim Koehler
Google (2019)

Abstract

We introduce a method for serving models that estimate reach and demographics of cross-device
online audiences. The method assigns virtual people identifiers to events. The reach of a set of
events is estimated as a simple count of distinct virtual people assigned to these events. This
allows efficient serving of reach models at large scale. We formalize what it means for a reach
model to be actionable and prove that any actionable reach model is equivalent to some virtual
people model. We present algorithms for encoding reach models with virtual people and show that
a wide variety of modeling techniques can be implemented with this approach.