Using Machine Learning to Improve Brand Management in an Online Environment

Authors

  • Tetiana Iankovets Department of Marketing, State University of Trade and Economics, Kyiv, Ukraine
  • Marina Järvis Department of Business Administration, Tallinn University of Technology; Estonian Entrepreneurship University of Applied Sciences, Tallinn, Estonia
  • Olexander Fomin Department of automation, electronics and telecommunications, Educational and Research Institute of Information Technologies and Robotics, National University, Yuri Kondratyuk Poltava Polytechnic, Poltava, Ukraine
  • Svitlana Chernobrovkina Department of Marketing, National Technical University, “Kharkiv Politechnic Institute”, Kharkiv, Ukraine
  • Sofiia Shvets NinjaTech AI, 100, Los Altos, CA, United States

DOI:

https://doi.org/10.32479/irmm.20649

Keywords:

Machine Learning, Brand Management, Content Personalization, Marketing Strategies, Social Outreach, Artificial Intelligence

Abstract

The artificial intelligence (AI) solutions are used to personalize content, analyse consumer behaviour, and automate marketing processes. Studying the impact of machine learning (ML) on brand management (BM) helps to understand its role in improving the companies’ competitiveness in the global market. The aim of the study is to assess the ML’s impact on the BM effectiveness of leading companies from different countries for 2020-2023. The research employed the following methods: econometric methods, including multiple linear regression, panel data analysis, and comparative analysis of BM effectiveness between companies from different countries. The study confirmed the significant ML’s impact on BM effectiveness. Companies that actively use AI have higher social reach and positive reviews. Adidas demonstrates the highest BM Score (99.21), confirming the effectiveness of ML strategies in marketing. Amazon (85.51) and Apple (86.81) also have stable results due to personalized content and analysis of customer behaviour. Alibaba leads in social engagement (SE = 16.87%), which helps to engage customers. Burberry (PR = 68.40%) and Almarai (PR = 70.66%) have high levels of positive reviews, increasing consumer trust. Faster response times improve customer loyalty. It was found that companies that invest in content personalization and consumer behaviour analysis achieve better financial results and higher customer loyalty. Investment in social interaction and fast processing of customer requests are positively correlated with the overall success of the brand. The uniqueness of the study is that the proposed model quantitatively assesses the impact of individual factors on the BM effectiveness. A comparative analysis of the effectiveness of AI-based BM between selected countries was conducted for the first time. Further research can focus on analysing the long-term effects of implementing ML in BM. An important direction is to assess the AI role in shaping consumer behaviour. As well as studying the impact of AI algorithms on the financial performance of companies in various sectors of the economy.

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Published

2025-10-13

How to Cite

Iankovets, T., Järvis, M., Fomin, O., Chernobrovkina, S., & Shvets, S. (2025). Using Machine Learning to Improve Brand Management in an Online Environment. International Review of Management and Marketing, 15(6), 118–125. https://doi.org/10.32479/irmm.20649

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Section

Articles