Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda

The rapid advancement of artificial intelligence (AI) offers exciting opportunities for marketing practice and academic research. In this study, through the application of natural language processing, machine learning, and statistical algorithms, we examine extant literature in terms of its dominant topics, diversity, evolution over time, and dynamics to map the existing knowledge base. Ten salient research themes emerge: (1) understanding consumer sentiments, (2) industrial opportunities of AI, (3) analyzing customer satisfaction, (4) electronic wordof-mouth-based insights, (5) improving market performance, (6) using AI for brand management, (7) measuring and enhancing customer loyalty and trust, (8) AI and novel services, (9) using AI to improve customer relationships, and (10) AI and strategic marketing. The scientometric analyses reveal key concepts, keyword cooccurrences, authorship networks, top research themes, landmark publications, and the evolution of the research field over time. With the insights as a foundation, this article closes with a proposed agenda for further research.

Automated summary

This study explores the existing literature on artificial intelligence (AI) in marketing through natural language processing, machine learning, and statistical algorithms, identifying ten salient research themes and analyzing the evolution of key concepts, keyword cooccurrences, and the research field over time using scientometric analyses. The article concludes with a proposed agenda for further research.