Google introduces new solution to prevent hidden ad tech fees

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• Confirming Gross Revenue gives buyers and publishers a safe way to verify that no hidden fees are taken

Google has introduced Confirming Gross Revenue, a new solution to give buyers and publishers a safe way to verify that no hidden fees are taken from their digital transactions when using Google Ad Manager. 

Publishers can use the Revenue Verification Report to see the aggregate gross revenue received from a specific buyer.

The buyer and publisher can then verify that the media cost from the buyer’s reporting matches the publisher’s gross revenue. If the numbers match, the buyer can confirm that their full media spend reached the publisher and no hidden fees were taken.

Google’s own demand-side platform, Display & Video 360, has come on board as an early tester, with Google also announcing they’re in communication with other demand-side platforms, sell-side platforms, publishers and agencies who will test the feature and provide feedback.

Philip Pollock, chief operating officer of Omnicom Media Group Australia, said: “OMG prides ourselves in being industry leading advocates for full supply chain transparency. 

“We believe this feature will be a great first step toward confirming that there are no hidden fees in programmatic buying, and having a seat at the table gives us the best opportunity to affect positive change for advertisers.” 

Anthony Katsur, CEO of IAB TechLab, said: “Greater transparency in the digital advertising supply chain through solutions like Confirming Gross Revenue is sorely needed. 

“That’s why we’ve made it a priority to invest in creating industry standards like ads.txt, sellers.json, DemandChain Object and buyers.json to help everyone raise the bar on trust in programmatic buying. 

“We look forward to working with Google on this privacy-forward solution and potentially incorporating these concepts into IAB Tech Lab’s standards portfolio.”

Confirming Gross Revenue only uses the data needed to confirm no hidden fees have been taken. To reduce the risk of user identification, the feature relies on aggregate gross revenue amounts rather than combining granular log-level data.

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