Evolution of Transparency in Digital Advertising
When it comes to true transparency in digital advertising, it appears that the industry can’t afford its own morals. All parties, from brands and agencies to tech and platform vendors themselves say that transparency into brand-suitable placements and fees are key values, but their actions render these sentiments somewhat toothless.
From a brand’s perspective, the idea of Transparency in digital advertising couldn’t be more straightforward: tell me where my ads appeared and how much I paid for those placements, and how much of my budget went to media and vendor fees? In reality, the answers require reporting and analysis, which, given the scale of today’s campaigns are enormously complex tasks to accomplish. That complexity also makes them very expensive.
Let’s start with reporting. The first task is getting accurate reports, which is no easy feat given the number of placements in the average campaign. Platforms like YouTube offer detailed reporting, but with 500 hours worth of video content uploaded every minute, reporting is a bit of a moving target.
Meanwhile, programmatic display campaigns are executed on an endless stream of websites that classify themselves as one thing or another, all of which can be captured on a report, but then what? Which brings me to the next challenge: Analysis.
Who should review the 100,000 YouTube videos and one million URLs of display placements that ran through programmatic media?
Brands expect to get that analysis from their agencies, who expect it from their tech partners, who expect it from the platforms, but they’re not set up to do that analysis.
Transparency into fees is another dicey area. A media agency and brand may agree to a set price of, say, 7 cents cost-per-view but we all understand that the underlying price of media is variable. Some placements may cost 4 cents, while others may cost 10 cents. Given the dynamics of the market, vendors actually assume quite a bit of risk when they agree to a set price. Pacing and fulfillment criteria will invariably force them to spend more than the agreed-to price for many impressions, but with luck, those high costs will be offset by lower cost impressions. It’s not unlikely for an agency to make 40-50 percent margin on some inventory, a number that may rankle a brand. Better to just aggregate the fees paid.
Why Tech Isn’t Rushing In
Learning how to capture placements and analyze brand suitability and fees are tech problems, and in an industry defined by machine learning, data science, AI, and so on, you may ask: why haven’t these problems been solved yet? Well, I would posit that the industry doesn’t really want transparency because it exposes some inconvenient truths.
Platforms like YouTube and Facebook are so huge that ensuring brand suitability is nearly impossible. A video’s content may be perfectly brand-suitable, but within minutes of posting an unrelated, but highly toxic conversation can begin in the comments section, turning it into a problematic placement for some brands. Moreover, nefarious players are well aware that the platforms have systems and reviewers watching out for specific images and language, and they’re motivated to stay one step ahead of them. Simply changing the spelling of a hate term may be enough to evade a detection system. A 99 percent accuracy rate is, by all accounts, an excellent achievement, but that 1 percent also means millions of bad placements are out there.
Besides, even if the platforms could do a placement-by-placement analysis, what would that do to their Section 230 protection of the Communications Decency Act?
Agencies might be able to do that work but are they incentivized to do so? Let’s say an agency executes a campaign to target adult females and an analysis shows that 20% of the ads were aligned with children’s content. The agency will have little incentive to inform the client that it missed the targeting goals by that degree. Even if they’re willing to report on misaligned targets, it’s a laborious task to accomplish and they’ll rightly want to be compensated for their efforts.
Brands, on the other hand, want to achieve campaign scale at as low a cost as possible, and that doesn’t leave a lot of leeway in the budget to invest in contextual alignment technology which assists brands with brand suitable placements. From their perspective, brand suitability should be assumed, just as one assumes that the food in a grocery store or restaurant has already been vetted by the owners and is safe for consumption. In reality, there’s a lot of infrastructure built into food safety, with thousands of inspectors visiting processing facilities every day. That cost is spread out among millions of consumers, however, so it’s barely noticeable. Besides, customers value the safety those inspectors and processes provide.
Transparency Needs to Evolve
Transparency needs to evolve. We all want brands to have confidence their ads targeted the right people in suitable placements, but how are we going to get there? As is always the case in our industry, dialogue drives innovation. This is a conversation which is difficult to have amongst so many constituents with differing incentives. Scale and meaningful transparency can work against one another, and reconciling them requires all parties to make financial commitments and deal honestly with inconvenient truths that are easier to keep swept under the rug. Once we have this conversation, innovation will follow.
In order to get that conversation going, here are three questions we need to ask ourselves:
How can I use the placement reports you sent me to understand whether or not they were brand-suitable and reached my target audience?
Parsing a list of millions of placements is nothing short of Big Data analysis, is this important enough to you to pay for it?
Are you willing to pull back the curtain on your execution strategy so that brands get an unvarnished look at where their ads ran?