Traditional market segmentation methods: classification and a brief overview

Abstract

The article analyses classical market segmentation methods in the context of the transformation of the business environment. It is established that despite significant changes in the methods of collecting and processing consumer data, classical segmentation approaches retain their relevance due to their conceptual clarity, universality, and suitability for strategic planning, especially in B2B markets. The paper summarizes and systematizes the main groups of segmentation methods, in particular traditional heuristic approaches (geographic, demographic, psychographic, behavioural, and segmentation by benefits), analytical statistical methods (cluster analysis, a priori segmentation, conjoint analysis, component analysis, perception mapping), as well as modern extensions of classical approaches (ABM, ICP, JTBD, RFM analysis, geodemographic models). It is proven that traditional segmentation methods provide ease of application and interpretation, but are characterized by a high level of heuristics and subjectivity. At the same time, analytical methods allow to reveal hidden patterns in large data sets and to form more objective segments, however, they require complex mathematical apparatus and qualitative data. Particular attention is paid to the integration of classical approaches with modern concepts, in particular the relationship between JTBD, ICP and ABM as sequential stages of forming an effective segmentation strategy. It is substantiated that the modern development of marketing involves a combination of heuristic and analytical approaches, which allows to increase the accuracy of targeting and the effectiveness of marketing decisions. The practical significance of the results obtained lies in the formation of a holistic view of the market segmentation tools and the possibility of its adaptation to the conditions of the digital economy. Prospects for further research are related to the integration of segmentation methods with artificial intelligence technologies and agent decision-making systems.