A New Approach to Real-Time Bidding in Online Advertisements: Auto Pricing Strategy

Shalinda Adikari () and Kaushik Dutta ()
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Shalinda Adikari: Department of Information Technology, University of Moratuwa, Moratuwa, Sri Lanka
Kaushik Dutta: Muma College of Business, University of South Florida, Tampa, Florida 33647

INFORMS Journal on Computing, 2019, vol. 31, issue 1, 66-82

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 a website 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.

Keywords: real-time bidding; demand-side platform; bid price; bid request; target audience; dynamic programming; winning rate (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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