Consumer microsegmentation based on machine learning: an overview of methods and Russian practice

This article reviews modern approaches to consumer microsegmentation using machine learning algorithms. It provides an analysis of clustering, supervised, and hybrid learning methods applicable to the segmentation of customer databases. Particular attention is given to the practical implementation of microsegmentation by Russian companies such as Ozon, Wildberries, Sber, and Tinkoff, where machine learning technologies are integrated into digital ecosystem platforms. Based on a review of domestic and international literature, the study identifies the strengths and limitations of various methods and outlines the prospects for the development of microsegmentation in the context of business digitalization. The findings may be of interest to professionals in marketing, data analytics, and digital transformation.