Optimizing Market Segmentation Granularity in RTB Advertising: A Computational Experimental Study

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

	Optimizing Market Segmentation Granularity in RTB Advertising: A Computational Experimental Study
	Qin Rui1,2,3 ; Yuan Yong1,2,3 ; Wang Fei-Yue1,4
	2016
会议名称	The 9th IEEE International Conference on Social Computing and Networking (SocialCom2016)
会议日期	2016
会议地点	USA
摘要	Real Time Bidding (RTB) is a novel business model of online computational advertising with the integration of Internet economy and big data analysis. It can help advertisers achieve the precision marketing through the market segmentation strategies of Demand Side Platforms (DSPs). Based on a mathematical programming approach, this paper studied DSPs’ strategies for market segmentation, and established a selection model of the granularity for segmenting RTB advertising markets. We proposed to validate our model using the computational experiment approach, and the experimental results show that: 1) with the increasing refinement of the market segmentation granularity, the total revenue has a tendency of a rise first followed by a decline; 2) the optimal granularity of market segmentation will be significantly influenced by the number of advertisers on the DSP, but less influenced by the number of ad requests. Our findings show the crucial role of market segmentation on the RTB advertising effect, and indicate that the DSPs should adjust their market segmentation strategies according to their total number of advertisers. Our findings also highlight the importance of advertisers as well as the characteristics of the target audiences in DSPs’ market segmentation decisions.
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/15441
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	1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences 2.Qingdao Academy of Intelligent Industries 3.Beijing Engineering Research Center of Intelligent Systems and Technology 4.Research Center of Military Computational Experiments and Parallel System, National University of Defense Technology
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Qin Rui,Yuan Yong,Wang Fei-Yue. Optimizing Market Segmentation Granularity in RTB Advertising: A Computational Experimental Study[C],2016.

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