DoubleVerify Expands Collaboration with LinkedIn to Reinforce Brand Safety Protections and Contextual Alignment

With this integration, DoubleVerify advertisers can further protect brand equity and maximize campaign performance for mutual customers on LinkedIn Audience Network

NEW YORK–(BUSINESS WIRE)–DoubleVerify (“DV”) (NYSE: DV), a leading software platform for digital media measurement, data, and analytics, today announced the launch of DV Authentic Brand Suitability and DV Custom Contextual solutions on the LinkedIn Audience Network. These two products empower advertisers to ensure their campaign impressions are delivered on inventory that aligns with their brand safety, suitability and contextual needs.

DV Authentic Brand Suitability goes beyond standard categories and keyword blocklist – offering customized protection that helps advertisers avoid unsafe and unsuitable content before placing a bid. DV Custom Contextual provides advertisers a scalable solution to reach the right audiences, at the right time – driving outcomes for brands.

DV’s Semantic Science, a proprietary contextual classification system, powers both DV Authentic Brand Suitability and DV Custom Contextual technology. DV’s Semantic Science team is responsible for developing one of the world’s most comprehensive ontology solutions — identifying over 200,000 language-independent concepts, using more than eleven million rules to determine the correct meaning of a word. The result is more accurate content classification and better protection and alignment, which enables stronger campaign performance for brands using solutions, like the LinkedIn Audience Network, for their marketing.

“Our work with LinkedIn underscores DV’s continued leadership position in optimizing media quality and performance holistically across the digital media landscape providing our advertisers the confidence to invest across channels and environments,” said Steven Woolway, EVP, Business Development at DoubleVerify. “LinkedIn is a leading platform for B2B digital advertising, and we are thrilled to collaborate to support brand suitability and contextual targeting.”

Today, advertisers can reach and engage a professional community of more than 875 million members on LinkedIn, helping them to drive actions that are relevant to their business. With the LinkedIn Audience Network, B2B advertisers can reach millions of targeted professionals who are active on trusted third-party publishers to boost performance across their advertising objectives, achieve better return on ad spend, and scale their message with multiple touchpoints.

“Through our work with DoubleVerify, we’re continuing to empower our customers to scale their marketing across our network of publishers to reach and engage a professional audience,” said Abhishek Shrivastava, VP of Product, LinkedIn. “The evolution of our collaboration reinforces our goal to foster a safe and trusted ecosystem with added controls to help customers drive better value from their campaigns.”

DV Authentic Brand Suitability and DV Custom Contextual are now available for all mutual LinkedIn and DV customers. This release builds on the company’s previous work with LinkedIn to help power its custom, network-wide brand safety floor and invalid traffic (“IVT”) protection that helps ensure advertisers are protected from universally unsafe content and IVT on the LinkedIn Audience Network.

For more information about DoubleVerify, visit https://www.doubleverify.com.

About DoubleVerify

DoubleVerify (“DV”) (NYSE: DV) is a leading software platform for digital media measurement and analytics. Our mission is to make the digital advertising ecosystem stronger, safer and more secure, thereby preserving the fair value exchange between buyers and sellers of digital media. Hundreds of Fortune 500 advertisers employ our unbiased data and analytics to drive campaign quality and effectiveness, and to maximize return on their digital advertising investments – globally. Learn more at www.doubleverify.com.

Contacts

Media:

Chris Harihar

Chris@crenshawcomm.com