Marketers are struggling to get a handle on cross-channel attribution, judging by several efforts now in progress.
For example, the Data & Marketing Association (DMA) has created a sample RFI and glossary, defining every term from “match rate” to “truth set.” And the Coalition for Innovative Media Measurement (CIMM) will release a white paper, “Best Practices in Multi-touch Attribution and ROI Analyses” during its Cross-Platform Media Measurement & Data Summit in New York on Feb. 16.
Now being developed with Sequent Partners, that paper will focus on attribution modeling, marketing-mix models and what CIMM calls “single-source analyses based on exposure and purchase data matched at the household level.”
Why this attention now? The purpose is to “bring some consistency and clarity,” to the wild-west environment that now prevails in the field, said Jane Clark, the CEO and managing director of CIMM, during a recent briefing.
One problem is that vendors and marketers use different language to describe the discipline. “We came to the conclusion that it’s still very early days,” Clarke said.
For this reason, marketers may not be getting the precise solutions they need.
Comparisons are difficult. In general, though, older data companies “are taking a bit more care in making sure they are doing it correctly,” Clarke said. Some newer ones may be developing probalistic algorithms that “can’t possibly be validated.”
She added that “even companies that you think are 100% deterministic are not really 100%.”
At the same time, many companies in this space are “buying each other.”
Then there are the “macro-level” data issues. In a recent paper titled “Best Practices in Cross-Device and Cross-Channel Identity Measurement,” CIMM defined these as:
MediaMath’s Ari Buchalter concluded in the paper that “Some of the data are … just perpetually inaccurate. People move. They create new log-ins. There’s a percentage of those data that are always inaccurate and out-of-date.”
Where does that leave the end-user marketer? Asking the following questions: “Where are you sourcing the data, how much is black box, can you figure out all sources, how often they’re refreshed and updated, and how solid and reliable they are? You can’t take it at face value,” Clarke said.
CIMM is also trying to “bring more granular measurement to television,” Clarke added. The question is: “Can you use these census-based measurements to get away from panels, and be able to link people across devices and offline and online media?”
Finally, cross-channel marketers have to cope with the privacy issue. Clarke cautioned marketers that “you’re as responsible as the vendor if you overstep the bounds into something that’s not a good use of the data.”
In its recent paper, CIMM said that “accuracy in the context of cross-device identification, is typically calculated as the number of matches and non-matches correctly identified, or the number of times a deterministic or probabilistic prediction was correct.”
However, CIMM added that “accuracy scores vary based on approach, and how this measure is calculated varies from solution to solution. As a rule, most accuracy scores do factor in non-matching predictions to calculate accuracy.”
One vendor commented that “the fact that numbers are being put out there that, in practice, count useful and non-useful matches as being equally valued is not helpful.”
CIMM advises marketers to:
The February summit will also feature updates on global cross-platform measurement, kids and teens, multi-platform TV and video.
Correction: Coca-Cola will be represented on a panel at the CIMM summit but will not be presenting research, as an earlier version of this column stated.