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IAS Tests 3P Content Block List Meta Optimisation Solution; Availability For Advertisers From Early 2025

MM Desk by MM Desk
October 11, 2024
in Advertising
A A
IAS Tests 3P Content Block List Meta Optimisation Solution; Availability For Advertisers From Early 2025

Integral Ad Science, one of the leading global media measurement and optimisation platforms, is currently testing a first-to-market optimisation solution for advertisers on Meta which will offer global advertisers the ability to automatically avoid placing ads next to content they deem unsuitable for their brand on Facebook as well as Instagram Feed and Reels, as aligned to industry standards.

Currently under testing, IAS’ third-party Content Block List solution for advertisers is open to IAS customers who currently use measurement for reels and feed solutions on Instagram and Facebook.

That being said, the first-to-market Meta optimisation solution for advertisers- IAS’ Content Block Lists will be available to all advertisers in early 2025.

As per Integral Ad Science, the company has completed rigorous testing for Content Level Block Lists to validate performance improvements and brand suitability and paired with Total Media Quality (TMQ), it aims to provide end-to-end campaign support for advertisers across Facebook and Instagram Feed and Reels with measurement and optimisation.

Optimisation with Content Block Lists provides global advertisers with:

  • Social Optimisation: Social Optimization for Content Block Lists enable advertisers to ensure that impressions are delivered to brand suitable ad adjacencies. This solution empowers advertisers with proactive pre-screen capabilities at the content level on Facebook and Instagram Feed and Reels.
  • Custom, Dynamic Control: Advertisers can create custom Content Block Lists based on industry-aligned standards and an expansive catalog of contextual categories. IAS Content Block Lists offer more granular control than publisher level block lists and are able to keep up with the pace of content creation to ensure suitability.
  • Seamless Activation: Advertisers can automatically avoid running next to content they deem unsuitable across Facebook and Instagram Feed and Reels using an easy, one-time activation within IAS Signal.
  • Industry-leading AI-Driven Multimedia Technology: Only IAS analyzes content at the frame-by-frame level, combining image, audio, and text signals for best-in-class accurate classification.
  • End-to-end Campaign Support: Global advertisers can pair Optimization with Total Media Quality for Meta across 28 languages, across Facebook and Instagram Feed and Reels, to further scale the brand suitability of their digital media investments.

Commenting on the development, Lisa Utzschneider, CEO, Integral Ad Science, said, “As the first provider to test this solution with Meta, we are delighted to enable advertisers to drive engagement and reach users in brand suitable, contextually relevant environments across Meta’s platform. Our Content Block Lists improve media quality while reducing brand risk for advertisers by providing industry-aligned tools that enable them to avoid content they deem unsuitable and safely scale their campaigns.”

To this, Samantha Stetson, Vice President- Client Council and Industry Trades, Meta, added,  “This solution demonstrates our continued commitment to provide global advertisers more tools to support their brand suitability goals,”  . “Alongside Meta’s inventory filter for Feed and Reels, we’re excited to give advertisers even more control over where their content appears on our platform.”

Earlier, in April 2024, IAS had expanded its Brand Safety and Suitability Measurement product to include the category of misinformation aligned to industry standards across Facebook and Instagram Feed and Reels.

And in February 2024, it had made available its AI-driven Total Media Quality (TMQ) Brand Safety and Suitability Measurement across Facebook and Instagram Feed and Reels in partnership with Meta to offer advertisers coverage for advanced, industry-leading measurement.

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