MediaMath launches contextual ad targeting for video with IRIS.TV

Tuesday, June 11th, 2019 
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MediaMath Launches Contextual Ad Targeting Solution for Video in Partnership with IRIS.TV

  • Enables Industry to Activate Contextual Video Data at Scale

NEW YORK — MediaMath, acclaimed independent programmatic company for marketers, today announced the launch of the industry’s first buy-side video contextual targeting solution for programmatic video. MediaMath is providing brands and agencies the ability to target video campaigns based on the context of each video being watched, enabling them to reach engaged audiences while viewers are watching correlated and relevant programming. Additionally, the offering empowers brands to better protect their audiences by selecting the types of content they do not want to be associated with, enhancing overall targeting, control and brand safety.

The new solution is made possible through a partnership with IRIS.TV, the market leader in video intelligence and programming solutions. IRIS.TV provides deep and unique integrations with publisher content management systems (CMS) and major video players across the industry with their existing video recommendations product. By activating contextual data on video inventory, IRIS.TV is able to surface the context of video content to ad servers in any video playback environment – enabling MediaMath marketers to reach relevant and relatable content.

“Publishers and advertisers can now match premium content with relevant video advertising in real-time and across multiple platforms, ensuring a better overall experience for the viewer,” said Mike Fisher, vice president, Advanced TV & Video, MediaMath. “Our new solution ensures a more engaged and valuable audience for publishers, while advertisers enjoy better targeting and control of their message.”

Key features of the solution include:

  • Video Infrastructure Agnostic: Access to categorized publisher video content hosted in any CMS and video supply streamed via any video player.
  • Video Context Targeting: Target video ads in context to what audiences are watching in real-time – placing ads adjacent to relevant content.
  • Cross-Screen Buying Capabilities: Scale across desktop, mobile web and OTT devices to optimize all aspects of brand marketing.

IRIS.TV has long been a pioneer in video personalization technology, utilizing machine learning to help media companies program video streams of contextually relevant editorial content on their owned-and-operated properties. As a result, publishers have increased user engagement, ad inventory, and revenue yield. With this partnership, users will now have a relevant advertising experience that matches their relevant content experience.

“Marketers and brands are demanding the capabilities to align their digital video advertising with relevant content that audiences are watching,” said Richie Hyden, Co-Founder & Chief Operating Officer, IRIS.TV. “We are excited to be working with MediaMath to launch this industry leading solution for our publisher and broadcaster customers to help them grow the size and value of their video audiences.”

MediaMath is leading an industry-wide effort to create an accountable and addressable supply chain through an alliance of agencies, brands, tech companies and publishers designed to provide long term sustainable solutions for a clean digital media supply. The partnership with IRIS.TV will for the first time MediaMath will address the issues surrounding contextual targeting and brand messaging relevance across video supply. MediaMath is championing a revitalized digital ecosystem focused on the availability of brand safe, fraud free and viewable inventory.

MediaMath is committed to cleaning the supply chain and blocking unauthorized and counterfeit inventory made available through non-certified sellers in order to promote a safe and transparent buying ecosystem. The new solution empowers all parties to have a more accountable role in monitoring and delivering on a better experience through the supply chain.

Links: IRIS.TV; MediaMath