That’s bad news for advertisers, who waste millions targeting these “people” every day and have no ability to audit these numbers.
It’s a good reminder that we need to continue to work on transparent solutions to reduce fraud, both inside the walled gardens and in the exchange-based programmatic universe.
The term “data transparency” may be the most overused ad industry phrase of 2018, yet I’m not sure it’s clear to many of us what that even means. Media has quickly shifted to a data-led buying approach, bringing massive improvement in reach and efficiency, but it has also perpetuated fraud across the digital ecosystem.
While sellers have tried to respond via initiatives such as ads.txt, MOAT and IAS, the data used in programmatic advertising has yet to receive the same attention, even though it also accounts for hundreds of millions of dollars in fraud and waste.
It doesn’t have to be this way.
Some simple questions when buying data segments can ensure that an advertiser/agency is receiving the quality data that they’ve been sold.
Can you prove these are real humans?
If a data provider is unwilling or unable to guarantee delivery of verified human programmatic IDs, you should pass. When billions of bots are purged from data platforms, you have to wonder how they got into the platform in the first place, and how much money was spent on that data before it was discovered. Campaigns marred by bot-ridden IDs underperform and waste tons of dollars for the advertiser.
What is the provenance of the segment?
Your data partner must be able to tell you how their IDs made it into your requested segment. Looking for a segment of pop music super fan, auto intenders? You need to know how the DMP has defined those pop music super fans AND auto intenders. And they need to prove that the audience isn’t scaled up through irrelevant IDs or probabilistic matching that dilutes the efficiency.
How is the segment being verified?
While inventory fraud has been addressed head-on, an audience-led buying environment will require a verification model for audience segments. How will your data partner insure transparency and verification of the IDs in every segment actioned?
This is a perfect use case for blockchain technology, where each ID and its provenance can be written to the blockchain as a smart contract and verified by advertiser, agency, publisher and data partner.
Make sure that your data partner explains if and how they verify their segments and the methodology for publishing that verification in a public-facing way. Beware of those in the industry pushing for loose self-regulation and making statements about how the largest, most entrenched industry players can be trusted to root out the fraud.
It’s worth asking these questions no matter how big or well-known your data partner may be. Although there are certainly some great next-gen data companies with strong verification technology who are working very hard to clean up the industry and pursue a new set of best practices, the “big guys” certainly can’t be considered the stalwarts of transparency in this industry. From global social platforms to legacy DMPs, the headlines are full of stories uncovering fraud from top to bottom.
When we hold our data suppliers responsible for the legitimacy of their data, we will all be doing our part to bring daylight to an industry still desperately in need of true transparency.