ARTIFICIAL INTELLIGENCE IN CUSTOMER JOURNEYS: A BIBLIOMETRIC STUDY

Abstract

With the growing relevancy of Artificial Intelligence (AI) in marketing, there is a need for extant research to investigate how AI has contributed to enhancing customer journeys. Thus, this research aims to accumulate knowledge about AI and customer journeys from published works. The Scopus database was scraped by using specific keywords. Initially, 864 papers were found for the period between 2000 to 2022. After careful investigation, 213 publications across 47 countries published by 666 scholars were retained for the bibliometric analysis. Accordingly, both Bibiloshiny and VOSViewer were utilised for deriving co-authorships, co occurrences, citations, bibliographic coupling and co-citations analysis. The average number of citations per article was 9.592, whilst the collaboration index was 3.37. The findings mainly revealed key authors, affiliations, total citations, key journals, and most published countries using performance analysis and science mapping techniques. Co-occurrence under all keywords produced seven important clusters such as machine learning, learning algorithms, recommender systems, sales, commerce, decision support systems and electronic commerce. On the other hand, co-citations based on cited sources classified four clusters connected to the journal of consumer research, computers in human behaviour, journal of marketing research and management science. The article contributes to academics and practitioners understanding of the prominent AI applications to customer journeys in the pre-purchase, purchase and post-purchase stage. Therefore, this research provides a unique reference for future research to extrapolate AI technologies that amplify customer experience.