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A new approach to real-time bidding in online advertisements: Auto pricing strategy

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dc.contributor.author Adikari, S
dc.contributor.author Dutta, K
dc.date.accessioned 2023-03-27T03:03:42Z
dc.date.available 2023-03-27T03:03:42Z
dc.date.issued 2019
dc.identifier.citation Adikari, S., & Dutta, K. (2019). A New Approach to Real-Time Bidding in Online Advertisements: Auto Pricing Strategy. INFORMS Journal on Computing, 31(1), 66–82. https://doi.org/10.1287/ijoc.2018.0812 en_US
dc.identifier.issn 1091-9856 en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/20813
dc.description.abstract Abstract. Real-time bidding (RTB) for digital advertising is becoming the norm for improving advertisers’ campaigns. Unlike traditional advertising practices, in the process of RTB, the advertisement slots of a mobile application or awebsite are mapped to a particular advertiser through a real-time auction. The auction is triggered and is held for a few milliseconds after an application is launched. As one of the key components of the RTB ecosystem, the demand-side platform gives the advertisers a full pledge window to bid for available impressions. Because of the fast-growing market of mobile applications and websites, the selection of the most pertinent target audience for a particular advertiser is not a simple human-mediated process. The real-time programmatic approach has become popular instead. To address the complexity and dynamic nature of the RTB process, we propose an auto pricing strategy (APS) approach to determine the applications to bid for and their respective bid prices from the advertising agencies’ perspective. We apply the APS to actual RTB data and demonstrate how it outperforms the existing RTB approaches with a higher conversion rate for a lower target spend. en_US
dc.language.iso en en_US
dc.publisher Institute for Operations Research and the Management Sciences en_US
dc.subject real-time bidding en_US
dc.subject demand-side platform en_US
dc.subject bid price en_US
dc.subject bid request en_US
dc.subject target audience en_US
dc.subject dynamic programming en_US
dc.subject winning rate en_US
dc.title A new approach to real-time bidding in online advertisements: Auto pricing strategy en_US
dc.type Article-Full-text en_US
dc.identifier.year 2019 en_US
dc.identifier.journal INFORMS Journal on Computing en_US
dc.identifier.issue 1 en_US
dc.identifier.volume 31 en_US
dc.identifier.pgnos 66-82 en_US
dc.identifier.doi https://doi.org/10.1287/ijoc.2018.0812 en_US


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