Retail analytics has become a cornerstone of modern retail strategy, fueled by rapid technological innovations and the digital transformation of traditional retail environments. This paper reviews 563 documents indexed in Scopus, critically evaluating current trends and emerging challenges in retail analytics. The analysis is structured around four key dimensions: artificial intelligence and machine learning, big data and data analytics, data-driven retail, and data-driven decision-making. By synthesizing the literature, this study identifies strategic opportunities and future research directions essential for leveraging retail analytics to enhance customer experience, optimize operations, and sustain competitive advantage in physical and digital retail landscapes. The findings aim to guide researchers, data scientists, and industry professionals in addressing practical and theoretical challenges in this evolving field.
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