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arXiv · 2602.14815

Revenue Guarantees in Autobidding Platforms

Ioannis Caragiannis·Anders Bo Ipsen·Stratis Skoulakis
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Abstract

Motivated by autobidding systems in online advertising, we study revenue maximization in markets with divisible goods and budget-constrained buyers with linear valuations. Our aim is to compute a single price for each good and an allocation that maximizes total revenue. We show that the First-Price Pacing Equilibrium (FPPE) guarantees at least half of the optimal revenue, even when compared to the maximal revenue of buyer-specific prices. This guarantee is particularly striking in light of our hardness result: we prove that revenue maximization under individual rationality and single-price-per-good constraints is APX-hard. We further extend our analysis in two directions: first, we introduce an online analogue of FPPE and show that it achieves a constant-factor revenue guarantee, specifically a $1/4$-approximation; second, we consider buyers with concave valuation functions, characterizing an FPPE-type outcome as the solution to an Eisenberg-Gale-style convex program and showing that the revenue approximation degrades gracefully with the degree of nonlinearity of the valuations.

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Ioannis Caragiannis, Anders Bo Ipsen, Stratis Skoulakis. 2026-02-16. Revenue Guarantees in Autobidding Platforms. https://arxiv.org/abs/2602.14815

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