We describe an algorithm to identify and target end-users based on their gender in a true big-data environment. We are utilizing a large number of data points originating from hundreds of millions of devices and thousands of applications daily. We use this data to derive a metric related to the probability of each individual device belonging to a female or male person. While such approaches are not new, the implementation in a real-time, big-data environment is challenging and requires continuous investment in data-science know-how and hardware set-up. Consequently, this whitepaper ends up with a claim for a neutral validation solution to justify those investments from AdTech companies and therefore higher CPM prices for the industry.

Based on Adello’s experience in serving over 500 customers worldwide since 2008, this paper serves to offer practical advice on setting up a mobile programmatic campaign to achieve the very best possible results and performance.

Adello is a media-buying platform that is unique in its ability to harnesses the power of machine-learning technology to deliver mobile advertising to the right customer at the right time and location. The traditional approach of programmatic media buying using audience segments is limited because the impressions of large groups of individuals are bundled together, selected, and then priced based on the average performance of each segment. Adello delivers results through a two step process that enables optimization at the individual impression level.