Exploring new mechanisms for demand-side platforms in real time bidding markets

Rui Qin, Yong Yuan, Xiaochun Ni, Feiyue Wang
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引用次数: 1

Abstract

When online advertising met the big data technology, programmatic buying has become more and more popular, in which Real Time Bidding (RTB) is regarded as one of the most important formats of programmatic buying advertising. In RTB advertising markets, there is a two-stage auction process for each ad impression, in which Demand-Side Platforms (DSPs) adopt a two-stage resale model to get their revenues. Thus, for each DSP, how to design effective auction mechanisms in the two-stage auction process so as to get higher revenues for both itself and its advertisers has become a critical issue. This paper aims to study this issue, and propose a new bidding and pricing mechanism for the DSP. We also utilize the computational experiment approach to evaluate our proposed mechanism, and the experimental results show that our new mechanism can improve the revenues of both the DSP and the advertisers.
探索实时竞价市场中需求方平台的新机制
当网络广告遇到大数据技术,程序化购买越来越受欢迎,其中实时竞价(Real Time Bidding, RTB)被认为是程序化购买广告最重要的形式之一。在RTB广告市场中,每个广告印象都有一个两阶段的拍卖过程,其中需求方平台(dsp)采用两阶段转售模式来获得收入。因此,对于每个DSP来说,如何在两阶段的拍卖过程中设计出有效的拍卖机制,从而为自己和广告商获得更高的收益就成为了一个关键问题。本文旨在对这一问题进行研究,并提出一种新的DSP竞价定价机制。我们还利用计算实验的方法来评估我们提出的机制,实验结果表明,我们的新机制可以提高DSP和广告商的收入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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