IRLGFeb 23, 2022

A Real-World Implementation of Unbiased Lift-based Bidding System

arXiv:2202.13868v14 citations
Originality Incremental advance
AI Analysis

This work addresses a practical problem for the online advertising industry by making lift-based bidding more adoptable, though it is incremental as it builds on existing lift-based methods.

The paper tackled the suboptimal performance of traditional bidding strategies in real-time bidding ad auctions by proposing an unbiased lift-based bidding system that aligns with current billing rules, achieving increased profitability for both DSP providers and advertisers through real-world experiments.

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

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