ML is a tool that when used for programmatic advertising can adjust bidding and targeting decisions based on historical data.
LifeStreet’s Prediction Engine uses ML to continuously learn from campaign data by identifying the patterns and signals belonging to your most valuable users. This information is collected and processed to help our DSP make better bidding, targeting and campaign optimization decisions.
Whether its user engagement, in-app purchases, or user lifetime value, our machine learning models learn what makes a valuable user to you and bids dynamically for each impression opportunity for each user.
Every time a bid request comes in, we run many models to make a final decision on things like:
- If we show the ad, how likely are they to install?
- Which campaign should we show?
- If the user installs the app, how likely will they be to make an IAP?
- Which ad group will have the highest yield?
- How similar is this user to existing user cohorts?
The answers to all of these questions help us bid effectively (i.e., the right user at the right price) to drive advertiser ROAS.