Predictive Bidding

Predictive Bidding uses machine learning models to forecast the likelihood that a specific impression will lead to a conversion. By analyzing historical data, user signals, time of day, and device context, the system determines how much an advertiser should bid in real time.

For example, a DSP may recognize that users browsing fashion sites at night on mobile devices are 30% more likely to convert. The algorithm automatically increases bids for these impressions while reducing spend on less valuable ones.

This AI-driven approach eliminates guesswork, improves efficiency, and ensures that every euro invested contributes to measurable performance gains. Predictive bidding is one of the key applications of AI in programmatic advertising today.

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