<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The global cosmetics market is dynamic and significant in size. Cosmetic products’ market is constantly expanding its influence to different target audiences and covers all classes of consumers. Marketing strategy of cosmetics corporations exists on different levels: main (global) and adapted (for the region or definite country). Generally, it connects with different influencing factors. Based on this, the main aim of this study is to identify and evaluate the key factors globally and evaluate the same for the Ukrainian market. To collect data about global tendencies authors accumulated existing statistical data, annual reports and scientific papers on this topic. For receiving results and collecting data about Ukrainian consumers, close-ended questionnaires were used as a method of collecting preliminary information. Results were classified, most important key success factors were highlighted and then machine learning techniques were used to provide an analysis of correlation. Our results demonstrated that despite the general difference of financial well-being of consumers in USA, Canada and European countries, Ukraine does not differ in consumer preferences by price, as a main factor. For sure it should be noticed, that price is the most influential in third world countries, but Ukrainian market has its own more influential specific factors.</p>
</abstract>

The global cosmetics market is dynamic and significant in size. Cosmetic products’ market is constantly expanding its influence to different target audiences and covers all classes of consumers. Marketing strategy of cosmetics corporations exists on different levels: main (global) and adapted (for the region or definite country). Generally, it connects with different influencing factors. Based on this, the main aim of this study is to identify and evaluate the key factors globally and evaluate the same for the Ukrainian market. To collect data about global tendencies authors accumulated existing statistical data, annual reports and scientific papers on this topic. For receiving results and collecting data about Ukrainian consumers, close-ended questionnaires were used as a method of collecting preliminary information. Results were classified, most important key success factors were highlighted and then machine learning techniques were used to provide an analysis of correlation. Our results demonstrated that despite the general difference of financial well-being of consumers in USA, Canada and European countries, Ukraine does not differ in consumer preferences by price, as a main factor. For sure it should be noticed, that price is the most influential in third world countries, but Ukrainian market has its own more influential specific factors.

Identification of the Factors Influencing the Cosmetic Products Market (Ukraine Case)

Taras Shevchenko National University of Kyiv

Studies in Business and Economics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The global cosmetics market is dynamic and significant in size. Cosmetic products’ market is constantly expanding its influence to different target audiences...

Identification of the Factors Influencing the Cosmetic Products Market (Ukraine Case)

Publié en ligne: 15 mai 2023

Pages: 328 - 341

DOI: https://doi.org/10.2478/sbe-2023-0018

Mots clés
cosmetic products market, product strategy, consumer behaviour patterns, factor analysis, machine learning methods

© 2023 Svitlana Sviderska et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Identification of the Factors Influencing the Cosmetic Products Market (Ukraine Case)

Publié en ligne: 15 mai 2023

Pages: 328 - 341

DOI: https://doi.org/10.2478/sbe-2023-0018

Mots cléscosmetic products market, product strategy, consumer behaviour patterns, factor analysis, machine learning methods

© 2023 Svitlana Sviderska et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
cosmetic products market, product strategy, consumer behaviour patterns, factor analysis, machine learning methods