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.
