On the Coordination of Value-Maximizing Bidders

While the auto-bidding literature predominantly considers independent bidding, we investigate the coordination problem among multiple auto-bidders in online advertising platforms. Two motivating scenarios are: collaborative bidding among multiple bidders managed by a third-party bidding agent, and strategic bid selection for multiple ad campaigns managed by a single advertiser. We formalize this coordination problem as a theoretical model and investigate the coordination mechanism where only the highest-value bidder competes with outside bidders, while other coordinated bidders refrain from competing. We demonstrate that such a coordination mechanism dominates independent bidding, improving both Return-on-Spend (RoS) compliance and the total value accrued for the participating auto-bidders or ad campaigns, for a broad class of auto-bidding algorithms. Additionally, our simulations on synthetic and real-world datasets support the theoretical result that coordination outperforms independent bidding. These findings highlight both the theoretical potential and the practical robustness of coordinated auto-bidding in online auctions.

💡 Research Summary

The paper investigates a coordination problem among multiple auto‑bidding agents that compete in repeated second‑price auctions on online advertising platforms. While most prior work on auto‑bidding focuses on a single advertiser’s objective—maximizing conversions or revenue subject to a Return‑on‑Spend (RoS) constraint—real‑world settings often involve several advertisers or many campaigns that could benefit from coordinated bidding. The authors formalize two motivating scenarios: (1) a third‑party bidding agent that manages several advertisers jointly, and (2) a single large advertiser that runs many distinct campaigns, each with its own auto‑bidding algorithm.

In the model, N auto‑bidders participate in T auction rounds. In each round t, bidder i draws a private value v_{i,t} from a continuous i.i.d. distribution F on