Artificial intelligence for smart bidding

Pratyush Shandilya, Laura Murphy and Fernando Perales
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Pratyush Shandilya: Data Scientist, Amplify Analytix, India
Laura Murphy: Amplify Analytix BV, The Netherlands
Fernando Perales: JOT Internet Media, Spain

Journal of AI, Robotics & Workplace Automation, 2023, vol. 2, issue 2, 153-164

Abstract: Growth in industry digitisation in recent years has resulted in consumers, manufacturers and service providers succumbing to the allure of the online platform, leading to the erosion of the long-standing supremacy of traditional businesses. With increasing competition among manufacturers both at local and global scope, it becomes crucial for them to make intelligent digital marketing decisions which could help get ahead of their competitors. Artificial intelligence (AI) has proven to be an effective medium for supporting decision-making in digital marketing. This paper discusses the application of contextual multi-armed bandits to optimise the bidding strategy used by digital advertisers in main search platforms. The highly scalable algorithm, apart from suggesting a winning strategy in an advertising auction, also enables clients to improve return on investment (ROI) using digital advertising.

Keywords: ad exchange; advertiser; contextual multi-armed bandits; digital marketing; publisher; reinforcement learning; AI (artificial intelligence); data-driven decision making (search for similar items in EconPapers)
JEL-codes: G2 M15 (search for similar items in EconPapers)
Date: 2023
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