Analyzing the Segmentation Granularity of RTB Advertising Markets: A Computational Experiment Approach

CASIA OpenIR > 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

	Analyzing the Segmentation Granularity of RTB Advertising Markets: A Computational Experiment Approach
	Qin, Rui; Yuan, Yong; Wang, Fei-Yue; Li, Juanjuan; Rui Qin
	2015-11
会议名称	National Conference of Social Media Processing (SMP2015)
会议录名称	Social Media Processing
会议日期	Nov. 16-17, 2015
会议地点	Guangzhou, China
摘要	Real Time Bidding (RTB) is an emerging business model of online computational advertising with the rise of Internet and big data. It can help advertisers achieve the precision marketing through evolving the traditional business logic from buying ad-impressions to directly buying the matched target audiences. As an important part of RTB markets, Demand Side Platforms (DSPs) play a critical role in matching advertisers with their target audiences via market segmentation, and their segmentation strategies (especially the choice of granularity) have key influences in improving the efficiency of RTB markets. This paper studied DSPs' strategies for market segmentation, and established a selection model of the granularity for segmenting RTB markets. We proposed to validate our model using a computational experiment approach, and the experimental results show that the market segmentation granularity has the potential of improving both the total revenue of all the advertisers and the expected revenue for each advertiser.
关键词	Real Time Bidding Demand Side Platforms Market Segmentation Granularity Computational Experiments Precision Marketing
收录类别	EI
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/11567
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	Rui Qin
推荐引用方式 GB/T 7714	Qin, Rui,Yuan, Yong,Wang, Fei-Yue,et al. Analyzing the Segmentation Granularity of RTB Advertising Markets: A Computational Experiment Approach[C],2015.

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