Toward Expressive and Scalable Sponsored Search Auctions

TL;DR

This paper proposes methods to enable more expressive bidding in sponsored search auctions, balancing complex advertiser goals with the need for fast, scalable winner determination in high-volume search environments.

Contribution

It introduces novel algorithms that support expressive bids while maintaining computational efficiency for large-scale search advertising auctions.

Findings

Supports more complex bidding strategies

Achieves fast winner determination at scale

Maintains high revenue potential

Abstract

Internet search results are a growing and highly profitable advertising platform. Search providers auction advertising slots to advertisers on their search result pages. Due to the high volume of searches and the users' low tolerance for search result latency, it is imperative to resolve these auctions fast. Current approaches restrict the expressiveness of bids in order to achieve fast winner determination, which is the problem of allocating slots to advertisers so as to maximize the expected revenue given the advertisers' bids. The goal of our work is to permit more expressive bidding, thus allowing advertisers to achieve complex advertising goals, while still providing fast and scalable techniques for winner determination.