New-To-Market TV Content Reporting Product Provides Buyers TV-Like Buying Opportunities and Publishers Unprecedented Video Analytics to Drive Revenue
Telaria, Inc., the complete software platform for publishers to manage premium video advertising, unveiled TV Content Reporting, a first-to-market product that enables premium publishers to better understand how advertisers value their most desired inventory.
“With the amount of data available today in digital advertising, the information transferred between publishers and advertisers is critical to success on both sides”
TV Content Reporting provides publishers with granular insight and analytics into the bidding and buying patterns of specific show titles, episodes, content categories and a more holistic view about the content advertisers want. With this insight, publishers create targeting directly in the platform, making specific content objects available to demand partners and driving higher value for their most desired inventory
This feature, in turn, enables demand partners to align with content in the same way they are accustomed to buying linear TV.
“The TV Content Reporting feature is a great example of how we’re enhancing what’s currently possible with connected TV advertising by incorporating tried-and-true broadcast best practices,” said Craig Berlingo, VP of Product at Telaria. “Inventory intelligence encompasses more than knowing who the audience is – publishers need to deeply understand how buyers assess their inventory and what is valuable to their objectives. The addition of TV Content Reporting makes our robust analytics suite even more adept at helping publishers earn the true value of their premium inventory.”
“With the amount of data available today in digital advertising, the information transferred between publishers and advertisers is critical to success on both sides,” said Laura Buchman, VP of Publisher Partnerships at Telaria. “Telaria’s TV Content Reporting product is an exciting development that gives publishers a better view of how buyers are interacting with their inventory, so they can iterate based on those learnings.”
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