Communication platforms are undergoing a transition from physical to digital spaces. The Internet has radically changed the business scenario wherein people have become the “media” for collaborating to share information. Practitioners have started using electronic word of mouth (eWOM) for consumer insight through text analytics, sentiment, hashtag analytics, and other machine learning tools. Due to the growing importance of the topic as a research area, it is vital to map the research domain. This paper uses performance analysis tools (quantitative and qualitative) and science mapping tools (conceptual and intellectual structures) for literature review and the identification of future research directions. The content analysis of emergent topics and themes offers directions for future researchers. Recommender systems, data mining (artificial intelligence and machine learning), semantics, and sentiment analysis are emergent topics. We contribute to the eWOM literature by canvassing state-of-the-art research and proposing future research directions.

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In marketing, personalization is the action of designing and producing in ways that resonate with customer preferences. Content and products that are personalized according to customer preferences can reduce customer fatigue and time in making choices, thereby decreasing their cognitive load. Despite its importance, the literature on personalized marketing remains fragmented due to the absence of a comprehensive review that consolidates the intellectual structure of the field. This study bridges this knowledge gap through a bibliometric review using performance analysis and science mapping. Through a comprehensive review of 383 publications, this study reveals the publication and citation trends, the most prolific authors, journals, and publications, and six major themes (i.e., personalized recommendation, personalized relationship, personalization–privacy paradox, personalized advertising, personalization concept and discourse in marketing, and customer insights in personalized marketing) that characterize the body of knowledge of personalized marketing. The study concludes with future research directions as ways forward for personalized marketing, wherein a focus on new‐age technologies involving artificial intelligence, big data, blockchain, internet of things, and wearables is encouraged to explore new ways to curate personalized experiences across online and offline channels.

Conversational agents are systems with human‐like features that can be deployed in service settings and are fast emerging as the future of online commerce. Considering the importance and proliferation of conversational commerce, it is opportune to take stock of the field's research from a bird's eye view to guide understanding of its current and future progress. In this regard, the goal of this study is to review the performance and intellectual structure of conversational commerce. To do so, this study conducts a comprehensive and systematic review of 722 publications on conversational commerce using the Scientific Procedures and Rationales for Systematic Literature Reviews protocol and a collection of bibliometric analysis techniques consisting of performance analysis and science mapping (e.g., content analysis, keyword co‐occurrence analysis, and bibliographic coupling). In doing so, this study reveals the performance (e.g., publication and citation trends, and top sources, publications, and authors) and the major theories and themes in the intellectual structure of the field. The study concludes with a conceptual framework depicting the constructs (e.g., antecedents, mediators, moderators, consequences, and enablers) of employing conversational agents for commerce and service delivery, as well as suggestions for its future research.

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