Data enrichment for incremental reach estimation
Venue
Google Inc. (2014), pp. 1-21 (to appear)
Publication Year
2014
Authors
Aiyou Chen, Jim Koehler, Art Owen, Nicolas Remy, Minghui Shi
BibTeX
Abstract
There is increasing interest in measuring the overlap and/or incremental reach of
cross-media campaigns. The direct method is to use a cross-media panel but these
are expensive to scale across all media. Typically, the cross-media panel is too
small to produce reliable estimates when the interest comes down to subsets of the
population. An alternative is to combine information from a small cross-media panel
with a larger, cheaper but potentially biased single media panel. In this article,
we develop a data enrichment approach specifically for incremental reach
estimation. The approach not only integrates information from both panels that
takes into account potential panel bias, but borrows strength from modeling
conditional dependence of cross-media reaches. We demonstrate the approach with
data from six campaigns for estimating YouTube video ad incremental reach over TV.
In a simulation directly modeled on the actual data, we find that data enrichment
yields much greater accuracy than one would get by either ignoring the larger
panel, or by using it in a data fusion.
