RTB-based mobile ad network
AdTheorent this morning unveiled what it described as the “industry’s first real-time learning and predictive modeling platform.” Dubbed the “Real-Time Learning Machine,”
the platform leverages machine-learning and predictive modeling to generate “on-the-fly” insights for mobile advertisers in real-time.
During a pre-release trial over the 2012 holiday shopping season, AdTheorent said the platform delivered average engagement levels in the “200-300%” range above industry norms for some undisclosed retail brands.
The platform, which was developed AdTheorent’s Chief Data Scientist Saed Sayad, analyzes 50,000 bid requests per second on a single server, filtering out bids with a low probability of click, conversion or awareness lift, the company said, adding that the system “learns from incoming bid requests and builds and modifies predictive models as it learns, applying such models in live campaigns to match each mobile advertisement with the optimum mobile impression.”
The company said campaigns tested to date generated “uplifts” as high as 500% over previous norms.
AdTheorent described the platform as the foundation of it’s “second generation mobile ad network.