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IAS and YouTube Brand Safety Solution Now Available for Advertisers

Dec 05, 2018

New IAS Offering Helps Reduce Brand Safety Risk in the Digital Ecosystem.

December 5, 2018 – New York, NY –   Integral Ad Science (IAS) and YouTube previously partnered to launch a beta test addressing the need for third-party brand safety and suitability measurement on the platform. Today the Brand Safety and Suitability solution moves out of beta, allowing IAS clients to use the technology to verify that ad placements on YouTube appear on content that aligns with their brand safety and suitability objectives.

The IAS solution incorporates a combination of machine learning and human review to constantly re-calibrate models, rather than solely relying on a static algorithm. Using this technique allows IAS to inform advertisers and YouTube of flagged content quickly.

“Universal McCann and our clients have been active participants with IAS in the YouTube brand safety beta. We’re excited that third-party brand safety verification will now be available to provide an additional layer of verification on YouTube for all advertisers,” said Joshua Lowcock, global brand safety officer and EVP/US chief digital and innovation officer, UM.

An extensive beta program that began last December, the Brand Safety and Suitability solution monitored campaigns across seven countries for over 50 advertisers. Prominent global brands including Verizon, Bayer Health, and Diageo were able to use IAS reporting to effectively adjust their brand safety requirements and ultimately see better outcomes on their YouTube ad placements.

“Solving brand risk within digital advertising will need stakeholders across the industry to work together on a cumulative solution – no one party can solve the issue alone,” said Nick Morley, EMEA MD at IAS. “In fact, this brand safety and suitability solution has seen great success in beta thanks to YouTube, IAS, and prominent brands working together to achieve a common goal.”

The machine learning model will continue to grow even now that the beta has closed. As more feedback is collected, the algorithm will analyse new content and the models will learn to identify videos deemed unsuitable so that brands can make real-time decisions around their campaigns.

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