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Fraud continues to plague the online advertising ecosystem, including on connected TV. But many in the ad tech industry would prefer to ignore the issue.
The “negative” paradigm of brand safety and verification technology is falling short in digital advertising. Recent research shows that the ad industry must adopt a “positive” verification model to thwart fraud.
The recent exit of Oracle’s Moat from the brand safety and ad verification market marks a significant turning point for the digital advertising industry.
For years, the market has been dominated by a trio of players: IAS, DV, and Moat—and a single technological design shared by all three: The underlying technology is designed to eliminate risks in the form of nonhuman traffic, nonviewable ads, and brand-unsafe content.
That approach, in other words, focuses on the negative, emphasizing what content should be avoided rather than what content should be embraced.
With Moat’s departure, the market is at a crossroads, presenting an opportunity to rethink and reshape the approach to brand safety and verification.
Let’s face it, AI is the new kid on the block, and it’s got some seriously impressive tricks up its sleeve. From crafting captivating stories with ChatGPT to conjuring stunning visuals with DALL-E, AI is shaking up the marketing world like a kid in a candy store.
But hold on a second, isn’t AI supposed to be the opposite of authentic? How can a machine, cold and calculated, help brands connect with real people? Well, buckle up, because AI is about to rewrite the script on ad verification.
So, if ever there was a time to invest in understanding the role of AI in ad verification, it is now.
It’s time for a paradigm shift in ad verification – one that moves from mere risk mitigation to active value creation; from avoiding the environments where brands shouldn’t appear to finding the ones where they should.
