u-Predict

User response probability modeling is an essential requirement for algorithmic decisioning and programmatic media buying. Used as a key determinator for yield optimization, advertiser metrics optimization, impression valuation and user response modeling, u-Predict is critical for Real Time Bidding success.

IPONWEB’s latest version of u-Predict, now in its 5th iteration, delivers amazingly accurate performance prediction from very low volumes of learning data. By learning rapidly on little volume, u-Predict dramatically removes the need for large test budgets and time allocations, used in traditional machine learning and yield / optimization methodologies.

uPredict also processes and learns from any number of user, publisher or advertiser data variables, to calculate accurate valuations and forecast performance. It has consistently proven to be significantly best in class in eCPM, CPC and CPA prediction across display and email media. It constantly updates and adjusts models to accommodate ever changing, time sensitive performance data

With more data, prediction and probability modeling becomes more and more accurate and u-Predict is able to operate across the entire process. Through a complex decisioning process that prioritizes the most telling and important variables when making a prediction decision, u-Predict represents a significant paradigm shift from traditional campaign centric targeting and optimization models.

u-Predict also features powerful analytics tools for understanding the value of audience segmentation attributes and diving deep into the nuances of decisioning, essential tools for evolving algorithmic and optimization performance.

u-Predict technology is the holy grail of the RTB space and replicating it requires years of specialist development. More significantly perhaps is that it requires testing on huge amounts of inventory for refinement. At IPONWEB we short-cut that incredibly complex learning process for our customers and are proud to say that the u-Predict product comfortably outperforms any other probability modeling or prediction technology currently used in the market.