BAT: Benchmark for Auto-bidding Task

Khirianova Alexandra, Ekaterina Solodneva, Pudovikov Andrey, Sergei Osokin, Egor Samosvat, Yuriy Dorn, Alexander Ledovsky, Yana Zenkova

Track: Economics, online markets and human computation

Keywords: Online auctions, advertising platforms, RTB, autobidding

TL;DR: We introduce a comprehensive benchmark for online advertising RTB task, featuring VCG and FPA auction formats, novel well-designed dataset, and baselines for key RTB challenges.

Abstract:

The optimization of bidding strategies for online advertising slot auctions presents a critical challenge across numerous digital marketplaces. A significant obstacle to the development, evaluation, and refinement of real-time autobidding algorithms is the scarcity of comprehensive datasets and standardized benchmarks.

To address this deficiency, we present an auction benchmark encompassing the two most prevalent auction formats. We implement a series of robust baselines on a novel dataset, addressing the most salient Real-Time Bidding (RTB) problem domains: budget pacing uniformity and Cost Per Click (CPC) constraint optimization. This benchmark provides a user-friendly and intuitive framework for researchers and practitioners to develop and refine innovative autobidding algorithms, thereby facilitating advancements in the field of programmatic advertising.

Submission Number: 1800