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Artificial intelligence for smart bidding

Author

Listed:
  • Shandilya, Pratyush

    (Data Scientist, Amplify Analytix, India)

  • Murphy, Laura

    (Amplify Analytix BV, The Netherlands)

  • Perales, Fernando

    (JOT Internet Media, Spain)

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.

Suggested Citation

  • Shandilya, Pratyush & Murphy, Laura & Perales, Fernando, 2023. "Artificial intelligence for smart bidding," Journal of AI, Robotics & Workplace Automation, Henry Stewart Publications, vol. 2(2), pages 153-164, December.
    • Handle: RePEc:aza:airwa0:y:2023:v:2:i:2:p:153-164
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    More about this item

    Keywords

    ad exchange; advertiser; contextual multi-armed bandits; digital marketing; publisher; reinforcement learning; AI (artificial intelligence); data-driven decision making;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • G2 - Financial Economics - - Financial Institutions and Services

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