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Eye of Riyadh
Technology & IT | Thursday 27 September, 2018 12:57 am |

RTB House develops a multi-layer brand safety mechanism, powered by natural language processing

RTB House – a global company that provides state-
of-the-art retargeting built on deep learning for top brands worldwide – announced
another big step towards solving one of the digital advertising industry’s most
problematic challenges with multi-layer brand-safety mechanism.

Brand safety is fast becoming a critical concern of the digital advertising space. Brands and
publishers must now ensure that their ads don’t run next to inappropriate content or within an
unsafe environment. This can mean content that contains extreme political views, fake news,
violence, catastrophe, or explicit content. Additionally, as computer hacking, and identity theft
are on the rise, there’s been an escalation in malware and phishing content on the internet.
To complicate this issue, every brand varies widely in their target audience, and must employ
a unique brand safety policy.

In response to this, RTB House has adapted its multi-layer brand safety mechanisms to tailor
itself for each brand’s policies. With natural language processing (analyzing web content in
real time) at its core, RTB House has developed a brand safety platform that can skim tens
of thousands of internet articles and websites daily, ensuring brand safety on a real-time
basis across much of the internet.

The core technology developed by RTB House is the Brand Profile layer, which prevents ads
from being served on websites or next to content that is not offensive in general but may
have negative effects from the perspective of advertisers’ brand-safety policies. It includes
three independent features:

Website category filters help brands to avoid website categories, which may be
sensitive from perspective of different brands, like for example: politically
controversial, user-generated content, file sharing, gambling, video stream, gaming,
manga and social services.

News filters which automatically blocks news containing specific non-brand-safe
keywords (both in URL addresses, in the content, or even in the meta page
descriptions). It is very helpful for companies which don’t want to be associated with
specific content (like automotive brands avoiding ads placement near to news about
car crashes or articles about alcohol). Since activating the natural language
processing algorithm, RTB House has already catalogued more than one million
articles and it’s constantly auditing more than 16,000 of the most popular global
articles every day – aiming to auditing more than 50,000 articles daily.

The RTB Blacklist allows brands to block their ads from specific, chosen URLs.

“We are the leading provider of technology
powered by natural language processing that addresses the brand-safety dilemma. Our
solution is a game changer,” says Tomasz Wnuk, Business Development Director Middle
East & Africa at RTB House. “We now have the ability to understand unstructured data and
analyze content on web pages before placing ads there. It then prevents the ads from being
displayed through offensive-content blocking. We also provide a combination of robust
security to prevent ad placements in unsafe environments,” he added.

On top of RTB House technology that can be tailored for specific brand needs, its
proprietary ad platform is powered with a multi-layer brand safety firewall that includes an
SSP and 3rd party solutions layer with leading brand-safety solutions from programmatic
inventory suppliers, and an Offensive content and malware layer that is complementary to
the first layer.

RTB House clients use the company’s solution to deliver ultra-personalized ads based on
behavior tied to users search tactics, browsing and basket behavior and other observations
within seconds across all devices and at just the right time to improve conversions and boost
sales. RTB House’s world-class retargeting platform currently handles over 2 million bid
requests per second, over 10 billion ad views per month and over 3.5 million daily clicks.

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