Machine Learning is a form of artificial intelligence (AI), which allows computers to learn tasks from previous data. Our technology finds the most optimal setup for your ad stack and adjusts parameters like floor prices in real time to achieve maximum yield.
The processors we built replace human guesswork while eliminating the natural constraints of manual inputs. Factors used to calculate and reach a perfectly optimized stack include: price floors, frequency caps, geolocations, devices, visibility, and over a dozen other variables we’ve carefully studied. This allows us to optimize for each user rather than overall audience segments.
The RevSense platform automates reporting and tag management, which fuels a critical function of RevSense: the yield optimization engine. By aggregating and standardizing data sets from demand partners, RevSense can make calculated decisions in real time.
The tag management system is responsible for executing the decisions our machine learning “brain” computes. The result is a hands-off platform that optimizes yield 24 hours a day.
RevSense provides a central location for all ad-ops data by aggregating adserver and demand partner data feeds into a single user interface. Before reaching our UI, RevSense converts the data to a standardized system of reporting.
This process accounts for ad server discrepancies, demand partner discrepancies, fill rates, and other information essential to obtaining accurate performance metrics.
Revsense is, in part, a tag management tool that automates every process, from tag creation to floor adjustments. Our header bidding solution brings the latest in bidding technology to publishers without the headaches.
The quick and easy integration process starts and ends with a publisher naming their placements. From there, the Revsense tool automatically generates, manages, and optimizes all ad tags in a publisher’s stack. We are compatible with every demand source, making it easy to convert waterfall setups or optimize existing header bidding integrations.