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

dc.contributor.authorAdikari, S
dc.contributor.authorDutta, K
dc.date.accessioned2023-03-27T03:03:42Z
dc.date.available2023-03-27T03:03:42Z
dc.date.issued2019
dc.description.abstractAbstract. 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.identifier.citationAdikari, 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.2018.0812en_US
dc.identifier.doihttps://doi.org/10.1287/ijoc.2018.0812en_US
dc.identifier.issn1091-9856en_US
dc.identifier.issue1en_US
dc.identifier.journalINFORMS Journal on Computingen_US
dc.identifier.pgnos66-82en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/20813
dc.identifier.volume31en_US
dc.identifier.year2019en_US
dc.language.isoenen_US
dc.publisherInstitute for Operations Research and the Management Sciencesen_US
dc.subjectreal-time biddingen_US
dc.subjectdemand-side platformen_US
dc.subjectbid priceen_US
dc.subjectbid requesten_US
dc.subjecttarget audienceen_US
dc.subjectdynamic programmingen_US
dc.subjectwinning rateen_US
dc.titleA new approach to real-time bidding in online advertisements: Auto pricing strategyen_US
dc.typeArticle-Full-texten_US

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