Machine learning is the engine that powers programmatic ad buying. It makes ad buying decisions in real time and at scale.
Machine learning uses historical data to find the best app users, predict their actions and serve the right ad to drive post-install engagement.
ML is only as good as the data you feed it. Feed it biased data, it’s useless and will not scale. Examples of biased data include whitelists/blacklists, fraud and accidental clicks.
Liftoff’s unbiased ML is trained to learn only from comprehensive, clean and accurate data. By training on complete data, Liftoff’s unbiased ML learns to adapt to the changing app ecosystem and finds new pockets of performance in a dynamic app ecosystem.
Liftoff’s unbiased ML filters through data to find all of the best real users who intend to use your app.
Paces your daily ad spend to see all users throughout the entire day
Filters out 13% of bid requests that are fraudulent or suspicious
Blocks accidental clicks (30% of all clicks)Liftoff ML enriches bid request data to create detailed user profiles, giving Liftoff a better understanding of the user it’s bidding on. This is how Liftoff processes a bid request.
Acquisition is just one part of user LTV. The other is retention. Keep your users engaged and create loyalty with re-engagement, which is run on the same powerful ML platform.
Hear mobile app marketing experts from Liftoff discuss the impact of ML on the mobile app industry.
Learn how Coupang scaled their re-engagement campaign resulting in 270.6% increase in impressions.
Read our largest and most in-depth report of the year for the latest mobile user acquisition trends to help you plan the year ahead.
The popular mobile gaming studio received a significant increase in long-time, high-value users thanks to lookalike targeting by Liftoff.
