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

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进控制与自动化团队

	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
会议日期	Nov. 16-17, 2015
会议地点	Guangzhou, China
关键词	Real Time Bidding Demand Side Platforms Market Segmentation Granularity Computational Experiments Precision Marketing
英文摘要	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.
会议录	Social Media Processing
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/11567]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
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]. 见:. Guangzhou, China. Nov. 16-17, 2015.