According to Visual IQ's data, between August and October 2012, 94% of online display advertising spend went to placements where the last-click CPA was at least 70% higher than Visual IQ's calculated TrueCPA, showing how undervalued the online display advertising was with only last-click metrics. Yet looking at October to December 2012, only 52.4% of online display ad spend went to such ads. On a few occasions, online display ads were overvalued, with 0.6% of Visual IQ's clients' display ads having a CPA Skew of 70% or more between August and October, jumping to 6.6% of ads during the holiday season.
"With our clients, we look at the data the way they see it, which is generally last click, and we compared that to what we have, which is the data we're discussing now and how different those can be," said Brian Suh, director of analytics for Visual IQ. "Then we transition to, instead of using last as a reference point, they would use our metrics, which accounts for cross-channel and all the multiple touchpoints."
The data Visual IQ analyzed was, therefore, not a reflection of what clients were actually doing (which was generally using the Visual IQ TrueCPA), but was a look at what they would have seen if they had used traditional last-click metrics.
Comparing the August to October time frame to the October to December 2012 time frame, online display ads were slightly more accurately valued during the holiday season, as the deal- and discount-heavy display ads contributed more conversions.
"The trend that we noticed during the holiday season was that last click was getting slightly more accurate," said Suh. "I describe it as 'we are less incorrect than we were before,' but we're still pretty darn incorrect. From what we can tell, it was really driven by the deal-based nature. If you think about Black Friday or Cyber Monday, they are huge deal days and there are huge discounts being advertised there, which makes sense with the data."
As clients turn to the tools provided by Visual IQ, and other cross-channel marketing analytics companies, Muller and Suh hope attribution metrics can become more standardized and accurate industry-wide.