When solving for user-level attribution, 97% of the data collected are not clicks, not TV spots, they’re programmatic display views.
Add clicks, impressions, tv spots, etc together…create a pie chart, and you’ll see 97% plus or minus a few points are display views.
Viewability for viewability’s sake is good. But connecting user-level viewability to outcomes is really the key.
White washing viewability at an aggregate level versus a user-level: will keep you stuck in the old days.
Connecting bolt-on user-level viewability to attribution is nearly impossible. Many have tried.
But user-level attribution with built-in viewability is seamless, frictionless, and automatic to attribution.
Meaning, any display ad that isn’t viewable does not even enter the attribution credit equation.
Because attribution is like a balloon: if the falsehood of viewability or the lie of fraud takes up space in the balloon…it robs credit from the actual tactics creating and accelerating demand.
If you allow fraud and viewability to stay in the balloon of attribution, it’s like a massive tumor taking up space.
Viewability is complicated. C3 has been performing viewability since 2009, and this is perhaps the best explanation of viewability unpacked.
P&G’s Marc Pritchard said that 75 cents of every dollar P&G spent in digital media never reached the consumer. His math is pretty close.
Here’s why 49% of user-level attribution is solved with built-in viewability:
97% of all campaign data = programmatic display impressions
51% of those programmatic display views are not viewable (source: C3 Metrics).
Here’s The Math
(97% x 51%) = 49%
49% of your campaign data is wrong before you even begin.
If you have viewability built-in to user-level attribution, 66% of attribution is solved.
Want data-driven ROI?
Built-in viewability is a huge piece of the pie.