Machine learning in marketing: Recent progress and future research directions - Editorial for the Special Issue “Machine Learning in Marketing”

Aug 2, 2026

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Decision-making in marketing has been transformed over the past decade through algorithmic prediction, shaping choices about which consumers to target and which offers to present. Machine learning (ML) supports marketing intelligence and efficiency while also creating new challenges for the marketing landscape. This editorial summarizes recent progress and future research directions by reviewing typical ML applications in marketing, introducing a guiding framework, positioning related special-issue articles within it, and concluding with a research agenda to steer further work.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages12

Reading Time30 min

Introduction

Problem context: customer data and marketing decisions

Role of machine learning in marketing

Overview of the editorial’s scope

Typical ML applications in marketing

Guiding framework and positioning of articles

Future research agenda

VU Research Portal Machine learning in marketing: Recent progress and future research directions Herhausen, Dennis; Bernritter, Stefan F. ; Ngai, Eric W.T. ; Kumar, Ajay; Delen, Dursun published in Journal of Business Research 2024 DOI (link to publisher) 10.1016/j.jbusres.2023.114254 document version Publisher's PDF, also known as Version of record document license Article 25fa Dutch Copyright Act Link to publication in VU Research Portal citation for published version (APA) Herhausen, D. , Bernritter, S. F. , Ngai, E. W. T. , Kumar, A. , & Delen, D. (2024) . Machine learning in marketing: Recent progress and future research directions: Editorial for the Special Issue “Machine Learning in Marketing”. Journal of Business Research, 170, 1-11 . Article 114254. [https://doi.org/10.1016/j.jbusres.2023.114254](https://doi.org/10.1016/j.jbusres.2023.114254) General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. E-mail address: [vuresearchportal.ub@vu.nl](vuresearchportal.ub@vu.nl) [Download date: 01](Download date: 01) . Aug. 2026 Journal of Business Research 170 (2024) 114254 Contents lists available at ScienceDirect Journal of Business Research journal [homepage: www.elsevier.com/locate/jbusres](homepage: www.elsevier.com/locate/jbusres) | Machine learning in marketing: Recent progress and future research directions | | | | | --- | --- | --- | --- | | Editorial for the Special Issue “Machine Learning in Marketing” Dennis Herhausen a, *, Stefan F. Bernritter b, Eric W.T. Ngaic, Ajay Kumar d, Dursun Delene, f a Marketing, Vrije Universiteit Amsterdam, the Netherlands b Marketing, King’s Business School, King’s College London, United Kingdom c Information Systems and Operations Management, The Hong Kong Polytechnic University, Hong Kong d Operations, Data & Artificial Intelligence, EM Lyon Business School, France e Department of Management Science and Information Systems, Spears School of Business, Oklahoma State University, Stillwater 74078, OK, USAf Department of Industrial Engineering, Faculty of Engineering and Natural Sciences, Istinye University, Sariyer/Istanbul, Turkey | | | | | A R T I C L E I N F O | | A B S T R A C T | | | Keywords: Machine learning Privacy Algorithm Marketing Research agenda | | 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

FAQs

Why is machine learning increasingly important in marketing decisions?

Machine learning helps firms convert large customer data into prediction-based insights for decisions such as targeting and offer selection.

What benefits does algorithmic decision-making promise for marketing?

It promises marketing that is more intelligent, efficient, consumer-friendly, and ultimately more effective.

What does the editorial provide to guide future research?

It outlines recent progress, reviews common ML applications, proposes a guiding framework for the special issue, and ends with a research agenda for further study.

Aug 2, 2026

Upload by Liam