Learn Why MediaMath Selected Ocient for Next Generation Campaign Forecasting

After more than a decade as a leading advertising technology pioneer, New York City-based MediaMath needed to innovate quickly in the campaign forecasting space. With more than 3,500 advertisers relying on their demand-side platform and modernized ecosystem to solve complex marketing problems, MediaMath was already helping their clients deepen customer relationships across screens and around the world. But their advertising clients wanted the ability to scientifically leverage more granular campaign insights to forecast more accurately for future campaigns and reduce wasted or poorly targeted impressions.

The MediaMath demand-side platform processes six million bid opportunities per second, generating up to 12 petabytes of new records each day. As critical columns are analyzed, there can be over 7 trillion data points that may need to be evaluated in a forecast query. In the past, the industry standard was to deliver estimates of potential campaign reach, impressions, and spend by using smaller samples of data derived from data rollups. While customers could easily see approximate results, general trends, and big-picture analysis, they were missing those needle-in-a-haystack insights into their advertising campaigns that are so essential for maintaining a competitive edge.

MediaMath was uniquely positioned to be the first to market with a solution that would allow advertising clients to plan their campaigns with higher resolution insights, which in turn would help them make more accurate predictions across engagement points, including connected devices like smart TVs – all with less waste and higher ROI. This solution would not only ensure they retained key accounts, but also unlock a huge potential for new business. It would operate at a huge scale and demand a huge increase in storage footprint and cost. It could also take a team of their best engineers up to a year to build.