A holistic review of customer experience research: topic modelling using BERTopic

Purpose This study consolidates the current state of knowledge in customer experience (CX) research by examining literature published over last 20 years (2003–2022). The purpose is to create a holistic snapshot through synthesis of extant CX research; and thereafter, leverage the snapshot to generate directions for future inquiry. Design/methodology/approach The study uses systematic literature review (SLR) using SPAR-4-SLR protocol to generate a set of 277 articles. We follow it up with scientometric analysis techniques of bibliographic coupling and betweenness centrality measurement. Finally, to extract topics from the full-text content of sampled articles, we carry out topic modelling using BERTopic. Findings The study unearths following insights: (1) the predominant underlying topics in extant CX research are: service experience, store brand marketing, mall and online shopping, fun and luxury marketing, brand equity and loyalty artificial intelligence (AI) and machine learning (ML) and augmented reality (AR) and virtual reality (VR); (2) bibliographic coupling suggests existence of six clusters in CX research. The study also showcases the nucleus of CX research, flagship research, major publication outlets and representative studies for each extracted topic. Research limitations/implications The paper introduces BERTopic to marketing scholars as a novel method of executing topic modelling and thereby, unearthing latent insights. Originality/value The study expands the body of knowledge on CX by applying three complementary analytical approaches: SLR, scientometric analysis and topic modelling using BERTopic.