When Transparency Isn’t Enough

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This year’s Advertising Week 2018 is packed with dozens of talks about issues and ideas that hinge on advertising data. Whether the conversation is about brand trust, safety or engagement or about marketing innovation, attribution, AI or effectiveness, clean data is a prerequisite. Data is the foundation upon which marketing leaders are shaping their visions of tomorrow, but today’s advertising data is hardly foundation-worthy. The data that powers digital advertising is a mess. It’s incorrect more than 45% of the time.

This is the first Advertising Week in years that hasn’t included sessions on viewability. That’s likely because the industry rallied to put solutions in place that have, for the most part, addressed the problem. Likewise, occurrences of fraud and brand safety threats have dramatically declined over the last couple of years. Behind these success stories, industry organizations like the IAB and DMA worked hard to establish initiatives, standards, metrics and benchmarks that brought transparency and resolution to these issues.

Meanwhile, the black box of data remains opaque and what’s coming out of it is wrong almost half of the time. In fact, when it comes to wasted impressions (thus wasted spend), data quality is a bigger problem than fraud or viewability. Clearly, the current state of data quality needs a lot more attention. Apparently, it could use a little more exposure as well.

In one of this week’s sessions, the Data Marketing Association (DMA) is presenting the details of its new data labeling initiative, a project with a noble goal of improving data quality (5pm on Monday). However, the initial charter simply calls for data vendors to disclose more details about the origins and processing of the data they sell. That’s not enough. The program seeks to increase data transparency but does nothing to ensure data accuracy. Transparency of data provenance or process is not a proxy for accuracy, but the DMA’s approach is leading marketers to think it is. A recent Factual survey showed “nearly all (95%) of location data buyers agree that data ‘transparency’ {about the data source} accurately indicates the quality of the data.” The association’s definition of transparency is misleading and runs contrary to media initiatives like Viewability and Fraud. Those initiatives called for transparent proof of how media actually scores. This time around, when it comes to data, little is currently being done to prove quality.

The DMA’s use of the term “verification” is also at odds with its use in the context of media initiatives. The organization’s medium-term plan is to establish a “third party check,” “verification,” or “certification that what’s on the label is accurate.” For clarity, a segment would be “verified” simply by being honest about the ingredients and process – details that will only help buyers assume that the data meets quality standards. Coming from an industry standards organization, this is an oddly shortsighted goal that’s likely to short-circuit any industry efforts to drive real accountability for the accuracy of data, in other words actual “verification”.

Once advertising data is labeled as the DMA prescribes, a data provider could simply buy data from a guy on the street corner for $10 and, so long as they admit as much on their data label, the segment would be considered “verified.” This is bound to mislead data users about what “verification” means in this context. “Verified” won’t have anything to do with accuracy or quality. Reversing this misstep later will be like pushing boulders uphill.

When you order a bottle of wine with your dinner, the cost will make up a significant part of the meal check. No matter where you’re dining, the waiter is going to have you taste it to ensure that it meets your expectations and that you’re not serving vinegar to your guests. Simply showing you a label that says the wine is from Napa Valley isn’t enough. In today’s advertising, the cost of data can easily add up to half of the CPM. It’s essential that it’s quality-tested, not just labeled to imply a level of quality.

Big brands are built on big ideas. Big ideas, now more than ever, are dependent upon big data. That’s a lot of weight to bear if the data isn’t viable. Data accuracy can’t be a long-term goal. The DMA needs to re-evaluate its data labeling charter to make actual, truly-verified data quality its immediate objective. “Transparency” must mean proof, as it does in every media context. Data “verification” must mean an actual evaluation of data accuracy, not just a certified label touting where the data came from. We as an industry may not get a widely adopted methodology for data accuracy verification the first time, but at least the baby steps would be pointed in the right direction.

Prioritizing accuracy will enable data buyers to choose data segments based on quality, not merely an implication of quality. It will naturally fuel significant improvements in campaign results, ROI and expectations. Most importantly, pertaining to Advertising Week’s agenda, prioritizing a fix to the widespread issue of data inaccuracy will establish a reliable foundation for the big ideas outlined by the inspiring, visionary speakers throughout the week.

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