Optimizing the Segmentation Granularity for RTB Advertising Markets with a Two-stage Resale Model

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	Optimizing the Segmentation Granularity for RTB Advertising Markets with a Two-stage Resale Model
	Qin, Rui; Yuan, Yong; Li, Juanjuan; Wang, Fei-Yue
	2016-10-09
会议名称	2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC2016)
会议录名称	Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC2016)
会议日期	Oct. 9-12, 2016
会议地点	Budapest, Hungary
摘要	Real Time Bidding (RTB) is an emerging business model and a popular research topic of online advertising markets. Using cookie-based big-data analysis, RTB advertising platforms have the ability to precisely identify the features and preferences of online users, segment them into various kinds of niche markets, and thus achieve the precision marketing via delivering advertisements to the best-matched users. The segmentation granularity used by such platforms, typically referred to as the Demand Side Platforms (DSPs), plays a central role in the effectiveness and efficiency of the RTB ecosystem. In practice, fine-grained user segmentations may lead to increased value-per-clicks and bid prices from advertisers, but at the same time reduced competition and possibly decreased bid prices in each niche market. This motivates our research on the optimal segmentation granularity to solve this dilemma faced by DSPs. Using a RTB market model with two-stage resales, we analyzed DSPs’ segmentation strategies taking the revenues of both advertisers and DSPs into consideration. We also validated our proposed model and analysis using the computational experiment approach, and the experimental results indicate that with the increasing of segmentation granularity, the weighted sum of the DSP and advertisers’ revenues tends to first rise and then decline in all weight-value cases, and the optimal granularity is greatly influenced by the value of weights. Our work highlights the need for DSPs of moderately using, instead of overusing, the online big data for maximized revenues.
关键词	Real Time Bidding Demand Side Platforms Market Segmentation Two-stage Resale Model Computational Experiment
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/19724
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者	Yuan, Yong
作者单位	The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
推荐引用方式 GB/T 7714	Qin, Rui,Yuan, Yong,Li, Juanjuan,et al. Optimizing the Segmentation Granularity for RTB Advertising Markets with a Two-stage Resale Model[C],2016.

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