omniture

Zefr expands its TikTok brand safety and brand suitability measurement to APAC advertisers

Zefr Inc.
2022-06-28 03:00 2147

LOS ANGELES, June 27, 2022 /PRNewswire/ -- Leading brand suitability company Zefr has expanded its brand safety and brand suitability post-bid measurement solution for in-feed ads on TikTok to advertisers in APAC, after previously being launched in North America (US and Canada), UK, EU (France, Germany, Italy, Poland and Spain), LATAM (Brazil and Mexico) and METAP.

Leading brand suitability company Zefr expands its TikTok brand safety and brand suitability measurement to APAC advertisers
Leading brand suitability company Zefr expands its TikTok brand safety and brand suitability measurement to APAC advertisers

This solution will provide advertisers with campaign insights into brand safety and brand suitability for their TikTok campaigns. These insights provide clients with third-party impartial reassurance that their investment is delivered next to content suitable for their brand, protecting brand reputation and mitigating risk. Clients can use these transparency and video-level insights to monitor their campaigns and optimize if needed.

"Zefr is thrilled to be expanding our TikTok brand safety and brand suitability measurement product to APAC customers," said Rich Raddon, co-Founder and co-CEO of Zefr. "Accurate and transparent brand safety and brand suitability measurement is critical for the industry, and we're thrilled to work with TikTok so that advertisers can have full transparency into their ad adjacencies."

This new post-bid brand safety and brand suitability measurement product gives brands deeper insights into their campaign analytics which can be mapped back to each of the 11 GARM categories. This solution will be paired with TikTok's pre-bid Inventory Filter solution, in order to activate the campaign measurement where advertisers will be able to access their TikTok campaign data on Zefr's Brand Safety and Brand Suitability dashboard.

Zefr's Cognition AI engine combines audio, text, and video frame-by-frame analysis with scaled human review and moderation. Backed by years of video training data, Zefr's machine learning approach goes far beyond just text and creator analysis, combining video-level analysis with scaled moderation specifically mapped to the GARM industry standards. Zefr's tech stack was built specifically for global video platforms with diverse languages, as traditional approaches to brand safety in the open web like semantics and keywords were insufficient for the highly dynamic and nuanced world of video.

CONTACT: Andrew Serby, andrew.serby@zefr.com 

Source: Zefr Inc.
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