REVENUE OPTIMIZATION IN REAL-TIME BIDDING BASED ADVERTISING FOR MOBILE DEVICES

Abstract

Real-Time Bidding (RTB) based advertising is becoming the new norm through which advertisers manage advertising campaigns. Unlike traditional online advertising practices, RTB maps impressions of advertisements on mobile applications or websites to a particular advertiser through a real-time auction. But this becomes challenging due to the impartiality in the data and the dynamism in the RTB ecosystem. Understanding how RTB differs from other advertising techniques is important as it has enormous potential to increase both the advertiser’s and the publisher’s revenues. In the RTB ecosystem, mobile app advertising has become the novel revenue generation channel through user and context targeted advertisements. The RTB ecosystem consists of two key entities –a publisher that places ads on end users’ devices and an advertiser that runs the advertising campaign via a Demand Side Platform (DSP). In this dissertation, we focus on optimizing advertising campaign operations both from the perspectives of publishers and DSPs.