New Jersey Institute of Technology, USA.
World Journal of Advanced Engineering Technology and Sciences, 2025, 15(01), 057-064
Article DOI: 10.30574/wjaets.2025.15.1.0189
Received on 24 February 2025; revised on 31 March 2025; accepted on 02 April 2025
Real-Time Bidding (RTB) has revolutionized digital advertising by enabling instantaneous transactions between publishers and advertisers through a complex technological ecosystem. This article examines the intricate data flows that power RTB, from the initial inventory signal to final ad delivery, all occurring within milliseconds. It explores the architectural components including Supply-Side Platforms, Demand-Side Platforms, and Ad Exchanges that facilitate these transactions. The article delves into optimization techniques such as parallel processing architectures, predictive caching, and real-time feature extraction that enable RTB systems to maintain exceptional performance. Critical security and privacy considerations are addressed, highlighting how data minimization, encryption protocols, and consent management have evolved in response to regulatory pressures. Performance metrics that guide ongoing system refinements are examined, demonstrating how bid response time, auction participation rates, win rates, and return on ad spend drive technical and business decisions in the programmatic landscape.
Real-Time Bidding; Programmatic Advertising; Data Flow Optimization; Privacy Compliance; Performance Metrics; Big Data; Real-Time Processing
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Rahul Gupta. Demystifying Real-time Bidding (RTB) data flows in AdTech. World Journal of Advanced Engineering Technology and Sciences, 2025, 15(01), 057-064. Article DOI: https://doi.org/10.30574/wjaets.2025.15.1.0189.