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StackAdapt Achieves Lower Fraud Rate than TAG’s Fraud Benchmark Study 2 Years in a Row.

StackAdapt has always recognized the importance of brand safety and fraud detection. We pride ourselves on our strong anti-fraud standpoint and take quality control very seriously. With partners such as Forensiq by Impact, StackAdapt provides quality assurance at all stages of campaign execution.

We are proud to announce that this strong emphasis on ad-fraud detection has resulted in StackAdapt achieving a lower overall fraud rate, beating both industry and TAG certified benchmarks two years in a row.

The Study

Annually, the Trustworthy Accountability Group (TAG) reports on quantitative and qualitative research that measures the rates of invalid traffic in TAG Certified Channels, in comparison to the industry average.

The 2018 Study measured general invalid traffic (GIVT) and sophisticated invalid traffic (SIVT) over 75 billion impressions of display and video inventory on Desktop, Mobile and In App devices. GIVT and SIVT are different flavours with different dangers. According to IAS insider, GIVT is like the white noise of fraud because it’s always on in the background. On the other hand, SIVT is like a cat and mouse game where fraudsters try to develop new forms of fraud that blend with legitimate inventory without being detected.

The Results

The industry average for overall fraud rate is 10.43%, while the average for TAG Certified Channels is 1.68%. StackAdapt surpassed both benchmarks with a lower overall fraud rate, for the second consecutive year.

StackAdapt’s traffic is 91% cleaner than the industry average and 41% cleaner than other TAG Certified Channels, which is one of the reasons StackAdapt received verified by TAG earlier this year.

We are so proud to provide this level of sophisticated fraud detection, and are continuously improving our fraud prevention tactics to ensure that our publisher partners and marketers operate in a trusted environment.

Want to run exceptional programmatic campaigns? Request a demo to learn more about StackAdapt.

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