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Machine learning and artificial intelligence use in marketing: a general taxonomy

Author

Listed:
  • Andrea Mauro

    (University of Rome Tor Vergata)

  • Andrea Sestino

    (University of Bari Aldo Moro)

  • Andrea Bacconi

    (Ecole Polytechnique - HEC Paris)

Abstract

The emergence of consumer-generated data and the growing availability of Machine Learning (ML) techniques are revolutionizing marketing practices. Marketers and researchers are far from having a thorough understanding of the broad range of opportunities ML applications offer in creating and maintaining a competitive business advantage. In this paper, we propose a taxonomy of ML use cases in marketing based on a systematic review of academic and business literature. We have identified 11 recurring use cases, organized in 4 homogeneous families which correspond to the fundamentals leverage areas of ML in marketing, namely: shopper fundamentals, consumption experience, decision making, and financial impact. We discuss the recurring patterns identified in the taxonomy and provide a conceptual framework for its interpretation and extension, highlighting practical implications for marketers and researchers.

Suggested Citation

  • Andrea Mauro & Andrea Sestino & Andrea Bacconi, 2022. "Machine learning and artificial intelligence use in marketing: a general taxonomy," Italian Journal of Marketing, Springer, vol. 2022(4), pages 439-457, December.
    • Handle: RePEc:spr:ijmark:v:2022:y:2022:i:4:d:10.1007_s43039-022-00057-w
    DOI: 10.1007/s43039-022-00057-w
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    1. Mariani, Marcello M. & Fosso Wamba, Samuel, 2020. "Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies," Journal of Business Research, Elsevier, vol. 121(C), pages 338-352.
    2. Harish Guda & Upender Subramanian, 2019. "Your Uber Is Arriving: Managing On-Demand Workers Through Surge Pricing, Forecast Communication, and Worker Incentives," Management Science, INFORMS, vol. 67(5), pages 1995-2014, May.
    3. Joanna Stavins, 2001. "Price Discrimination in the Airline Market: The Effect of Market Concentration," The Review of Economics and Statistics, MIT Press, vol. 83(1), pages 200-202, February.
    4. Vlačić, Božidar & Corbo, Leonardo & Costa e Silva, Susana & Dabić, Marina, 2021. "The evolving role of artificial intelligence in marketing: A review and research agenda," Journal of Business Research, Elsevier, vol. 128(C), pages 187-203.
    5. Corrado Cuccurullo & Massimo Aria & Fabrizia Sarto, 2016. "Foundations and trends in performance management. A twenty-five years bibliometric analysis in business and public administration domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 595-611, August.
    6. Beenish Tariq & Sadaf Taimoor & Hammad Najam & Rob Law & Waseem Hassan & Heesup Han, 2020. "Generating Marketing Outcomes through Internet of Things (IoT) Technologies," Sustainability, MDPI, vol. 12(22), pages 1-12, November.
    7. Erevelles, Sunil & Fukawa, Nobuyuki & Swayne, Linda, 2016. "Big Data consumer analytics and the transformation of marketing," Journal of Business Research, Elsevier, vol. 69(2), pages 897-904.
    8. Sheth, Jagdish & Kellstadt, Charles H., 2021. "Next frontiers of research in data driven marketing: Will techniques keep up with data tsunami?," Journal of Business Research, Elsevier, vol. 125(C), pages 780-784.
    9. Lucrezia Maria Cosmo & Luigi Piper & Arianna Vittorio, 2021. "The role of attitude toward chatbots and privacy concern on the relationship between attitude toward mobile advertising and behavioral intent to use chatbots," Italian Journal of Marketing, Springer, vol. 2021(1), pages 83-102, June.
    10. Ma, Liye & Sun, Baohong, 2020. "Machine learning and AI in marketing – Connecting computing power to human insights," International Journal of Research in Marketing, Elsevier, vol. 37(3), pages 481-504.
    11. Krystyna Jarek & Grzegorz Mazurek, 2019. "Marketing and Artificial Intelligence," Central European Business Review, Prague University of Economics and Business, vol. 2019(2), pages 46-55.
    12. Ming-Hui Huang & Roland T. Rust, 2021. "A strategic framework for artificial intelligence in marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 30-50, January.
    13. Campbell, Colin & Sands, Sean & Ferraro, Carla & Tsao, Hsiu-Yuan (Jody) & Mavrommatis, Alexis, 2020. "From data to action: How marketers can leverage AI," Business Horizons, Elsevier, vol. 63(2), pages 227-243.
    14. Vermeer, Susan A.M. & Araujo, Theo & Bernritter, Stefan F. & van Noort, Guda, 2019. "Seeing the wood for the trees: How machine learning can help firms in identifying relevant electronic word-of-mouth in social media," International Journal of Research in Marketing, Elsevier, vol. 36(3), pages 492-508.
    15. Sestino, Andrea & Prete, Maria Irene & Piper, Luigi & Guido, Gianluigi, 2020. "Internet of Things and Big Data as enablers for business digitalization strategies," Technovation, Elsevier, vol. 98(C).
    16. Brei, Vinicius Andrade, 2020. "Machine Learning in Marketing: Overview, Learning Strategies, Applications, and Future Developments," Foundations and Trends(R) in Marketing, now publishers, vol. 14(3), pages 173-236, August.
    17. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
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