Dynamic dual adjustment of daily budgets and bids in sponsored search auctions
Zhang, Jie1; Yang, Yanwu2; Li, Xin3; Qin, Rui1; Zeng, Daniel1,4
AbstractAs a form of targeted advertising, sponsored search auctions attract advertisers bidding for a limited number of slots in paid online listings. Sponsored search markets usually change rapidly overtime, which requires advertisers to adjust their advertising strategies in a timely manner according to market dynamics. In this research, we argue that both the bid price and the advertiser (claimed) daily budget should be dynamically changed at a fine granularity (e.g., within a day) for an effective advertising strategy. By doing so, we can avoid wasting money on early ineffective clicks and seize better advertising opportunities in the future. We formulate the problem of dual adjusting (claimed) daily budget and bid price as a continuous state discrete action decision process in the continuous reinforcement learning (CRL) framework. We fit the CRL approach to our decision scenarios by considering market dynamics and features of sponsored search auctions. We conduct experiments on a real-world dataset collected from campaigns conducted by an e-commerce advertiser on a major Chinese search engine to evaluate our dual adjustment strategy. Experimental results show that our strategy outperforms two state-of-the-art baseline strategies and illustrate the effect of adjusting either (claimed) daily budget or bid price in advertising. (C) 2013 Elsevier B.V. All rights reserved.
KeywordSponsored Search Auction Budget Adjustment Continuous Reinforcement Learning Dynamic Adjustment
WOS HeadingsScience & Technology ; Technology
Indexed BySCI ; SSCi
WOS Research AreaComputer Science ; Operations Research & Management Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems ; Operations Research & Management Science
WOS IDWOS:000330909700010
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Cited Times:13[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Huazhong Univ Sci & Technol, Sch Management, Wuhan 430074, Peoples R China
3.City Univ Hong Kong, Dept Informat Syst, Kowloon Tong, Hong Kong, Peoples R China
4.Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang, Jie,Yang, Yanwu,Li, Xin,et al. Dynamic dual adjustment of daily budgets and bids in sponsored search auctions[J]. DECISION SUPPORT SYSTEMS,2014,57(0):105-114.
APA Zhang, Jie,Yang, Yanwu,Li, Xin,Qin, Rui,&Zeng, Daniel.(2014).Dynamic dual adjustment of daily budgets and bids in sponsored search auctions.DECISION SUPPORT SYSTEMS,57(0),105-114.
MLA Zhang, Jie,et al."Dynamic dual adjustment of daily budgets and bids in sponsored search auctions".DECISION SUPPORT SYSTEMS 57.0(2014):105-114.
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