To optimize ROAS on Mail.ru, what advanced bidding strategy automatically adjusts bids based on predicted conversion probabilities, rather than fixed percentages?

To optimize Return on Ad Spend (ROAS) on Mail.ru, the advanced bidding strategy that automatically adjusts bids based on predicted conversion probabilities, rather than fixed percentages, is *target ROASbidding. Target ROAS bidding uses machine learning algorithms to analyze historical campaign data and predict the likelihood of a conversion for each individual user or ad auction. Based on these predictions, the system automatically adjusts bids in real-time to maximize ROAS while staying as close as possible to your specified target ROAS. Unlike fixed-percentage bid adjustments or manual bidding, target ROAS bidding considers a wide range of signals, such as user demographics, browsing behavior, device type, and time of day, to make more informed bidding decisions. By focusing on conversion probabilities, target ROAS bidding aims to bid higher for users who are more likely to convert and lower for those who are less likely, thus optimizing ad spend and improving overall ROAS. This dynamic optimization strategy allows for a much more granular and efficient allocation of budget compared to strategies that rely on static or rule-based bid adjustments.