  In display ad auctions of Real-Time Bid-ding (RTB), a typical Demand-Side
Platform (DSP)bids based on the predicted probability of click and conversion
right after an ad impression. Recent studies find such a strategy is suboptimal
and propose a better bidding strategy named lift-based bidding.Lift-based
bidding simply bids the price according to the lift effect of the ad impression
and achieves maximization of target metrics such as sales. Despiteits
superiority, lift-based bidding has not yet been widely accepted in the
advertising industry. For one reason, lift-based bidding is less profitable for
DSP providers under the current billing rule. Second, thepractical usefulness
of lift-based bidding is not widely understood in the online advertising
industry due to the lack of a comprehensive investigation of its impact.We here
propose a practically-implementable lift-based bidding system that perfectly
fits the current billing rules. We conduct extensive experiments usinga
real-world advertising campaign and examine the performance under various
settings. We find that lift-based bidding, especially unbiased lift-based
bidding is most profitable for both DSP providers and advertisers. Our ablation
study highlights that lift-based bidding has a good property for currently
dominant first price auctions. The results will motivate the online

Information Retrieval;Machine Learning