Nguyen, H, Gligorijevic, Dj, Borah, A., Adalinge, G., Bagherjeiran, A. (2023) “Practical Budget Pacing Algorithms and Simulation Test Bed for eBay Marketplace Sponsored Search”. AdKDD Workshop 2023 at the 29th ACM SIGKDD Conf. Knowledge Discovery and Data Mining (KDD 2023), August 6. – 10. 2021, Long Beach, CA, USA


Sponsored search program in online marketplaces is routinely offered to sellers allowing them the opportunity to enhance the visibility and performance of their items. Optimizing for different goals such are clicks or conversions, advertisers can run campaigns provided a budget constraint. However, without any control on the spend, campaigns with smaller budgets can run too briefly, failing to reach regions of high quality traffic. Moreover, the same lack of spending control can benefit a few dominating sellers, inducing a lack of competition that negatively affects the majority of sellers, the marketplaces’ revenue, and users experience. Budget pacing technique is a common tool used to control spend of ads campaigns that can tackle aforementioned challenges in a principled manner providing benefits to sellers, the online marketplace and users. In this paper we propose a simulation test bed based on real traffic of sponsored search program at eBay for accurate and safe evaluation of different budget pacing algorithms. We study several simple budget pacing algorithms, characterizing their effect under complex environmental constraints. As an important contribution, we describe an efficient test bed for offline simulations and propose a new simple and efficient budget pacing algorithm based on the campaigns’ remaining budget which can achieve improvements in many business metrics compared to the production benchmark.