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.
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