Beyond Isolated Bidding: Campaign-Channel Coordination for Global Optimal Returns in Online Advertising

Abstract

Automated bidding is a core component of modern online advertising systems. With the rapid proliferation of heterogeneous media channels, bidding strategies are required to handle ad requests across multiple channels in a unified manner to maximize total conversions while satisfying shared budget and cost-per-acquisition (CPA) constraints. Unlike existing approaches that decompose budget and CPA constraints into individual channels, we propose Campaign–Channel Coordinated Bidding (C3Bid), a bias-aware automated bidding framework that jointly optimizes final bidding decisions by coordinating campaign and channels under a unified campaign-level objective and constraints. The key insight of C3Bid is to leverage channel-wise estimation bias as an explicit coupling mechanism, where campaign-level and channel-level bids are combined through bias-aware weighting to produce the final bid. We theoretically show that the unified formulation admits a larger feasible solution space and achieves optimal expected conversions under shared constraints, while the proposed bias-aware coordination mechanism further improves channel scalability and robustness to cold-start scenarios. Extensive offline experiments and large-scale online A/B tests in a real-world advertising system demonstrate consistent and significant gains in conversions, budget utilization, and bidding stability under CPA constraints.