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Use cases of large language models in marketing analytics

Author

Listed:
  • Robbert, Katherine

    (Co-Founder and CEO, Trust Insights, USA)

  • Penn, Christopher

    (Co-Founder and Chief Data Scientist, Trust Insights, USA)

  • Wall, John

    (Partner and Head of Business Development, Trust Insights, USA)

Abstract

This paper explores the use cases of large language models (LLMs) in marketing analytics. The authors introduce generative artificial intelligence (AI) and its application in marketing, focusing on LLMs and their underlying architectures of transformers and diffusers. The paper discusses various use cases of LLMs in marketing, including marketing strategy analysis, data summarisation and recommendations, analysis and insights generation, bias reduction, increased productivity, trend spotting and risk management. It emphasises the importance of skilled team collaboration, subject matter expertise and careful preparation when implementing generative AI in marketing analytics. The authors also address the risks and measurement of performance associated with the use of generative AI in marketing.

Suggested Citation

  • Robbert, Katherine & Penn, Christopher & Wall, John, 2023. "Use cases of large language models in marketing analytics," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 9(3), pages 249-269, December.
    • Handle: RePEc:aza:ama000:y:2023:v:9:i:3:p:249-269
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    More about this item

    Keywords

    large language models (LLMs); marketing analytics; generative artificial intelligence (AI); marketing strategy analysis; data summarisation; recommendations; analysis and insights generation; bias reduction; increased productivity; trend spotting;
    All these keywords.

    JEL classification:

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

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