Country for PR: United States
Contributor: PR Newswire New York
Tuesday, June 28 2022 - 05:00
AsiaNet
Zefr expands its TikTok brand safety and brand suitability measurement to APAC advertisers
LOS ANGELES, June 28, 2022 /PRNewswire-Asianet/ --

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.

Photo - https://mma.prnewswire.com/media/1847553/Zefr_TikTok_Linkedin.jpg

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.