How to get the volumes you want in the post-IDFA world
Signals using non personal data rather than IDs to target our audience based on context
Programmatic performances offers the quality & flexibility you need to achieve and exceed your ROI target
Our auto-optimization system is powered by a Reinforcement Learning algorithm, a ML type belonging to the Deep Learning family algorithms. With rewards received in real-time into the system, our tech platform, Jenga, is able to optimize campaigns starting with the first conversion received.
With the help of Logistic Regression we can evaluate the probability of a specific event (install or post-install) will happening. With a trained set of data our system is able to filter the enormous volume of incoming requests and place a bid on the best promising ones only.
We are living the post-IDFA era so we can base our decisions on less user informations. We can of course execute a context-based targeting but we can also enrich the incoming requests with additional informations gathered from first and third party database before the bidding stage.
Our OpenRTB bidder is able to create dynamic creatives with different sizes and text variations. All creatives are rotated during the exploration stage and it keeps the best performing ones automatically in the next stages (optimization and scaling).
We can set several kinds of targeting. Our campaign specialists can fine tune your needs into our campaign settings in order to achieve your goals. Available targeting: User level, Device level, Geolocation level, Traffic source level and others.
Our anti-fraud filter protection is always enabled on both impressions and clicks layers and it works in real time. It's also updated regularly to assess the new threats that usually comes out.