具有多个kpi的广告服务

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Pub Date : 2017-08-13 DOI:10.1145/3097983.3098085

B. Kitts, M. Krishnan, I. Yadav, Yongbo Zeng, Garrett Badeau, Andrew Potter, Sergey Tolkachov, Ethan Thornburg, Satyanarayana Reddy Janga

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引用次数: 11

摘要

广告服务器必须满足许多不同的目标定位标准，而这些标准的组合往往会导致没有可行的解决方案。我们假设，广告商可能正在定义这些指标，以创建一种“代理目标”。因此，我们重新制定了标准的广告服务问题，我们试图尽可能接近广告商的多维目标，包括交付。我们使用一个简单的模拟来说明与约束和步调策略相比，该算法的行为。然后将该系统部署在美国最大的视频广告服务器之一中，我们展示了实时测试广告的实验结果，以及6个月的数百个广告的生产性能。我们发现实时广告服务器测试与模拟相匹配，并且我们报告了使用误差最小化策略在多kpi性能方面的显着收益。

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Ad Serving with Multiple KPIs

Ad-servers have to satisfy many different targeting criteria, and the combination can often result in no feasible solution. We hypothesize that advertisers may be defining these metrics to create a kind of "proxy target". We therefore reformulate the standard ad-serving problem to one where we attempt to get as close as possible to the advertiser's multi-dimensional target inclusive of delivery. We use a simple simulation to illustrate the behavior of this algorithm compared to Constraint and Pacing strategies. The system is then deployed in one of the largest video ad-servers in the United States and we show experimental results from live test ads, as well as 6 months of production performance across hundreds of ads. We find that the live ad-server tests match the simulation, and we report significant gains in multi-KPI performance from using the error minimization strategy.

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Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

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