Leveraging AI and Machine Learning for Advancing Marketing Research and Practice

Claude Assunt Mudre; Nhat Juschop

doi:10.69725/raida.v1i3.169

Authors

Claude Assunt M a. School of Business of University of Maryland, College Park, United States of America
Nhat Juschop b. Central Queensland University, Spencer Street, Melbourne 300, Australia

DOI:

https://doi.org/10.69725/raida.v1i3.169

Keywords:

Artificial intelligence, Machine learning, Marketing analytics, Consumer insights, Ethical AI

Abstract

Objective: This study examines the transformative potential of artificial intelligence (AI) and machine learning (ML) in marketing research and practice, highlighting their role in improving predictive accuracy, unlocking insights from complex data, supporting transparent analytics, and optimizing customer journey mapping. It also examines how the integration of human insights with AI contributes to the advancement of marketing theories and practices.
Methods: A comprehensive methodological framework has been designed to assess the interplay between the AI/ML-driven models and the key marketing constructs. Advanced statistical analyses were employed to ensure robust validation of theoretical and practical implications. Variables were operationalised using well-established instruments to ensure reliability and construct validity.
Results: The study identifies key trends and opportunities, showing how AI/ML technologies are reshaping marketing by addressing key challenges, enabling new capabilities and providing actionable insights. It also highlights gaps in current methodologies, calling for a nuanced understanding of their theoretical and practical applications.
Novelty: By bridging advanced AI/ML techniques with marketing theory, this research offers a fresh perspective on integrating technological innovation with human-centred insights. The study also addresses the importance of ethical frameworks and the interpretability of the models, thus paving the way for responsible AI-driven marketing.
Implications for Research: The findings encourage researchers to further explore the intersection of AI/ML and marketing, exploring underrepresented contexts, refining interpretative models and addressing ethics. Future research should aim to combine technological advances with consumer-centred and theory-driven approaches.

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Author Biographies

Claude Assunt M, a. School of Business of University of Maryland, College Park, United States of America

Claude Assunt M
School of Business of University of Maryland, College Park, United States of America
Nhat Juschop, b. Central Queensland University, Spencer Street, Melbourne 300, Australia

Nhat Juschop CFA AII
Central Queensland University, Spencer Street, Melbourne 300, Australia

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