Research on the Frequency Capping Issue in RTB Advertising: A Computational Experiment Approach
Qin, Rui; Yuan, Yong; Wang, Fei-Yue; Li, Juanjuan; Rui Qin
Conference Name2015 Chinese Automation Congress (CAC 2015)
Source PublicationProceedings of 2015 Chinese Automation Congress
Conference DateNov. 27-29, 2015
Conference PlaceWuhan, China
AbstractReal time bidding (RTB) is emerged with the rapid development and integration of Internet and big data, and it has become the most important business model for online computational advertising. In RTB-based advertising markets, Demand Side Platforms (DSPs) aim to help the advertisers buy ad impressions matched with their target audiences. Due to the existence of discount rate, the advertising effect may be diminished when displaying the advertisements multiple times to the same target audience. As such, frequency capping is widely considered as a crucial issue faced by most advertisers. In this paper, we mainly consider the frequency capping problems in RTB advertising markets, and establish a two-stage optimization model for advertisers and DSPs. Utilizing the computational experiment approach, we design two experiments to validate our model. The experimental results show that under different discount rates, the optimal frequency caps are different. Moreover, when considering all the discount rates, there exists an optimal frequency cap, at which the expected maximum revenue can be obtained in the long run.
KeywordReal Time Bidding Computational Advertising Frequency Capping Computational Experiment Approach Demand Side Platforms
Indexed ByEI
Document Type会议论文
Corresponding AuthorRui Qin
Recommended Citation
GB/T 7714
Qin, Rui,Yuan, Yong,Wang, Fei-Yue,et al. Research on the Frequency Capping Issue in RTB Advertising: A Computational Experiment Approach[C],2015.
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