A Computational Experiment Research on Segmenting RTB Advertising Markets
Qin, Rui; Yuan, Yong; Li, Juanjuan; Rui Qin
2015-12
Conference NameThe Seventh Chinese Conference on Social Computing
Source PublicationProceedings of the Seventh Chinese Conference on Social Computing
Conference DateDem. 11-13, 2015
Conference PlaceFuzhou, China
AbstractReal Time Bidding (RTB) is emerged with the rise of Internet and big data, and it realized precision marketing through the market segmentation strategies of Demand Side Platforms (DSPs). This paper studies DSPs' strategies for market segmentation, and established a market segmentation model to find the optimal granularity. We proposed to validate our model using a computational experiment approach, and the experimental results show that with the increasing of the market segmentation granularity, the total revenue has a tendency of a rise first and followed by a decline.
KeywordReal Time Bidding Demand Side Platforms Market Segmentation Granularity Computational Experiments Precision Marketing
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11579
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Corresponding AuthorRui Qin
Recommended Citation
GB/T 7714
Qin, Rui,Yuan, Yong,Li, Juanjuan,et al. A Computational Experiment Research on Segmenting RTB Advertising Markets[C],2015.
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