Machine learning in marketing: Recent progress and future research directions

Dennis Herhausen, Stefan F. Bernritter, Eric W.T. Ngai, Ajay Kumar and Dursun Delen

Journal of Business Research, 2024, vol. 170, issue C

Abstract: Decision-making in marketing has changed dramatically in the past decade. Companies increasingly use algorithms to generate predictions for marketing decisions, such as which consumers to target with which offers. Such algorithmic decision-making promises to make marketing more intelligent, efficient, consumer-friendly, and, ultimately, more effective. Not surprisingly, machine learning is a trending topic for marketing researchers and practitioners. However, machine learning also introduces important challenges to the marketing landscape. We discuss this development by outlining recent progress and future research directions of machine learning in marketing. Specifically, we provide an overview of typical machine learning applications in marketing and present a guiding framework. We position the articles in the Journal of Business Research’s Special Issue on “Machine Learning in Marketing” within this framework and conclude by putting forward a research agenda to further guide future research in this area.

Keywords: Machine learning; Privacy; Algorithm; Marketing; Research agenda (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:170:y:2024:i:c:s0148296323006136

DOI: 10.1016/j.jbusres.2023.114254

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