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Driving value in digital marketing: Navigating from applied machine learning to applied artificial intelligence

Author

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  • Subramanian, Vidya

    (Data Science, Google, USA)

Abstract

Today’s digital marketing analysts must navigate evolving regulations, stringent privacy policies, an assortment of tools, a fragmented technical landscape and the rapidly evolving fields of machine learning (ML) and artificial intelligence (AI). This paper addresses these challenges by proposing a comprehensive framework that splits the digital marketer’s role into three areas: marketing strategy, marketing operations and marketing technology. Within this context, the paper reviews how digital marketing analysts currently leverage ML and analytics. It then explores recent advancements in AI that are hoped will address the shortcomings associated with current ML solutions, before turning its attention to the shortcomings associated with AI. The paper underscores how digital marketing analysts need to weave AI strategically into all aspects of their role if they are to remain competitive and relevant in the Web3 era. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.

Suggested Citation

  • Subramanian, Vidya, 2025. "Driving value in digital marketing: Navigating from applied machine learning to applied artificial intelligence," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 11(2), pages 109-122, September.
    • Handle: RePEc:aza:ama000:y:2025:v:11:i:2:p:109-122
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    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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