IAS Announces First-to-Market Partnership with Nextdoor for AI-Powered Pre-Bid Brand Safety

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Integral Ad Science, a leading global media measurement and optimization platform, announced a strategic partnership with Nextdoor, the essential neighborhood network. IAS will now power Nextdoor's first-party brand safety tool as a provider of pre-bid Brand Safety and Suitability Optimization on the platform, assuring advertisers that impressions are delivered to brand suitable ad adjacencies.
IAS's pre-bid Brand Safety and Suitability Optimization uses AI-driven Multimedia Technology to provide advertisers with an additional layer of third-party transparency and suitability for their Nextdoor campaigns. Through this partnership, advertisers with managed accounts can run ads on Nextdoor's Newsfeed, reaching one-third of U.S. households, with the confidence that their ads will run in brand safe and suitable environments based on industry-aligned standards.
"This partnership represents a major milestone in bringing deeper transparency, trust, and control for advertisers spending on Nextdoor," said Jim Egan, SVP of Business Development of IAS. "By combining IAS's AI-driven Multimedia Technology with Nextdoor's strong content moderation capabilities, we're offering a new level of protection and performance for brands engaging in hyperlocal at scale advertising."
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IAS's pre-bid Brand Safety and Suitability Optimization for Nextdoor provides advertisers with:
- Trusted Third-Party Control: Nextdoor's brand safety tool, powered by IAS, enables advertisers to apply pre-bid blocking on their social campaigns, against 12 industry-aligned categories and 4 risk levels.
- Custom, Dynamic Control: Advertisers can avoid unsuitable content based on brand specific needs, across mobile and desktop web environments and more than 90 languages.
- Best-in-class Technology: IAS's AI-driven Multimedia Technology, layered with Nextdoor's proprietary moderation systems, enables advertisers to accurately classify content at scale through frame-by-frame analysis, combining image, audio, and text signals.
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