The Hybrid Market Segmentation of Electric Vehicles in Ukraine Using Data Science Methods Andrusyk Y. V., Guryanova L. S.
Andrusyk, Yevhenii V., and Guryanova, Lidiya S. (2025) “The Hybrid Market Segmentation of Electric Vehicles in Ukraine Using Data Science Methods.” The Problems of Economy 2:212–226. https://doi.org/10.32983/2222-0712-2025-2-212-226
Section: Mathematical methods and models in economy
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UDC 33.330.4
Abstract: The article examines the current issue of effective market segmentation for electric vehicles in Ukraine. This market, on one hand, demonstrates exponential growth, while on the other, it develops in the context of significant economic and social challenges, which shapes a unique consumer behavior. The carried out analysis showed that traditional segmentation approaches, which are primarily based on socio-demographic or price characteristics, are insufficient as they do not allow for understanding the deep drivers and motivations behind consumer choices. The aim of the study is elaboration and approbation of a comprehensive hybrid segmentation model that integrates objective quantitative market indicators and subjective psychographic and behavioral characteristics of consumers. The empirical basis of the work consisted of two datasets: structured data on the State registration of electric vehicles in Ukraine for the period from 2020 to 2025, and unstructured data that includes about 6000 text reviews from actual owners on leading Ukrainian automotive resources. To solve the tasks set, a comprehensive approach was applied, incorporating Data Science methods: descriptive statistics, data collection through Data Scraping techniques, natural language processing (NLP) for thematic modeling and sentiment analysis of the reviews, as well as cluster analysis using the k-means algorithm. In the first stage, the analysis of structured data allowed for the identification of key market trends and revealed a paradoxical polarization of demand: consumers predominantly choose either budget models with a small range or premium cars with maximum range. In the second stage, the analysis of unstructured data provided an explanation for this phenomenon, showing that the dominant usage scenario is "city trips", for which great autonomy is not critical. The synthesis of these two approaches in the final hybrid model allowed us to identify four fully-fledged, qualitatively distinct consumer segments:
• "Enthusiasts and Individualists" (33% of the market), for whom emotions from dynamics and design are a priority;
• "Pragmatic Optimizers" (28%), focused on the rational relationship between price and functionality for daily tasks;
• "Technological Leaders" (25%), who choose status, innovation, and technological superiority; and
• "Modern Family" (13%), for whom quality, comfort, and safety are key.
The research proves that only a hybrid approach, combining "what" (quantitative data) and "why" (qualitative data), allows for a complete and deep understanding of the modern market. The most important conclusion is that the largest market segment (33%) is influenced by emotional-image factors rather than purely rational ones, which provides market participants with practical tools for developing more accurate and effective marketing strategies.
Keywords: electric vehicle market, consumer segmentation, Data Science, cluster analysis, k-means method, natural language processing (NLP), sentiment analysis, structured data, unstructured data, consumer behavior, psychographic segmentation.
Fig.: 11. Tabl.: 3. Bibl.: 13.
Andrusyk Yevhenii V. – Postgraduate Student, Department of Economic Cybernetics and Systems Analysis, Simon Kuznets Kharkiv National University of Economics (9a Nauky Ave., Kharkіv, 61166, Ukraine) Email: andrusike@mail.com Guryanova Lidiya S. – Doctor of Sciences (Economics), Professor, Professor, Department of Economic Cybernetics and Applied Economics, V. N. Karazin Kharkiv National University (4 Svobody Square, Kharkіv, 61022, Ukraine) Email: guryanovalidiya@gmail.com
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