Beyond Single Slot: Joint Optimization for Multi-Slot Guaranteed Display Advertising

TL;DR

This paper introduces a joint optimization framework for multi-slot guaranteed display advertising, improving allocation efficiency and contract fulfillment over traditional single-slot methods.

Contribution

It presents a novel bipartite matching-based optimization approach with a contract roulette mechanism for multi-slot ad allocation, scalable for large-scale deployment.

Findings

28.99% increase in Average Revenue Per User in online tests

Significant improvements in merchant ROI and platform revenue efficiency

Enhanced contract stability demonstrated through DID analysis

Abstract

Guaranteed display advertising is crucial for platform monetization, yet existing methods often operate under a single-slot assumption, limiting their ability to optimize allocation across multi-slot page views. In this paper, we propose a novel joint optimization framework for multi-slot GD allocation, addressing key challenges such as slot-level redundancy, contract imbalance, and exposure concentration. Our approach formulates the allocation as an offline bipartite matching problem with a contract roulette mechanism for slot exclusivity and Page View constraints for impression control, and incorporates a scalable allocation optimization algorithm for efficient large-scale deployment. Extensive online tests on the Meituan advertising platform demonstrate that our method significantly improves merchant ROI, platform revenue efficiency, and contract fulfillment robustness. Specifically, online A/B tests show a 28.99% increase in Average Revenue Per User under 70% traffic, and DID analysis further indicates improved contract stability, demonstrating the strong applicability and effectiveness of our framework in real-world advertising deployments.