Digital attribution is the Holy Grail for digital analysts because on one hand, digital media promises unprecedented measurability while on the other hand it brings such level of fragmentation in measurement that it becomes counterproductive. This leads to duplicate conversions, focus on the last-click, invalid insights, and inefficiencies.
At the root of digital attribution challenge is multiplicity of ad serving technologies and analytical tools which measure the same event from different perspectives causing a disparate view of reality. To build upon the point using an example, display advertising analytical systems measure view-through events while web analytical systems only counts click-through events. Also, serving search and display through different systems causes double counting and inflation in conversions.
There is ample evidence that exemplifies the flaws in the existing last-click attribution model. On a CPG client, whenever display advertising was halted, the volume of conversions from search reduced significantly (though it had no impact on search conversion rates). This indicates that display media influences paid search performance but since paid search tends to operate at the bottom of the funnel, it tends to outperform display advertising on all metrics. In this case, the last-click attribution model recommends taking funds from display media and channeling them towards paid search but this could have a negative impact on overall campaign performance.
The current system fails to appreciate the impact of various digital channels on one another or measure the collective impact on business. An advertising effectiveness study (at the end of campaign!) showed significantly better improvement in awareness and purchase intent for those exposed to both display and eCRM communication as compared to those exposed to either of the tactics individually. But this retrospective knowledge was too late and came at the cost of six months of inefficiency.
Therefore, an ideal attribution system should measure individual and combined channel performance while providing real-time insights to arrive at optimal scenario and knowledge about points of diminishing returns. A web analytics solution could provide some of these insights if it could merge with an ad server or create capabilities to measure view-through behavior. And a vendor that could solve for this could be Google since they are vested in the Doubleclick ad server and have a strong web analytical system. In lieu of the same, a single tracking system with universal container tag is a better attribution solution compared to the current disparate measurement systems. However, most solutions that offer real-time insights fall short in providing actionable attribution models grounded in regression analysis. Also, majority of the real-time attribution solutions are threatened by cookie deletion. On the other hand, attribution solutions that use panel data can overcome the cookie challenges and can provide connectors with offline data but are hindered by small sample sizes and long turnaround times, making the insights archaic in the fast evolving digital space.
Thus, attribution is an industry-wide challenge that needs to be solved collectively by advertising fraternity, publishers, and measurement experts for the overall benefit of the industry and every player impacted by it. Because at the heart of robust attribution is the urge to invest more in the medium till it performs at its full potential!
Nirali Bhagdev recently joined Catalyst S+F as Director of Intelligence to initiate the analytics and data intelligence practice. She can be reached at firstname.lastname@example.org.
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