ABSTRACT. In this article, I cumulate previous research findings indicating that smart connected devices can assist data-driven decisions in retail livestreaming by articulating personalized shopping experiences as regards digital ownership across extended reality environments. I contribute to the literature on virtual immersive shopping experiences in metaverse environments by showing that contextual awareness and real-time performance data can typify immersive retail experiences, improving brand recognition. Throughout February 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “virtual immersive shopping experiences,” “predictive customer analytics,” “data visualization algorithms,” and “smart retailing technologies.” As I inspected research published between 2021 and 2022, only 83 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 16, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, MMAT, and ROBIS.

Keywords: virtual; immersive; shopping; metaverse; customer analytics; visualization

How to cite: Hudson, J. (2022). “Virtual Immersive Shopping Experiences in Metaverse Environments: Predictive Customer Analytics, Data Visualization Algorithms, and Smart Retailing Technologies,” Linguistic and Philosophical Investigations 21: 236–251. doi: 10.22381/lpi21202215.

Received 26 February 2022 • Received in revised form 20 May 2022
Accepted 24 May 2022 • Available online 30 May 2022

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