SOCIAL LISTENING PARADIGM IN THE SYSTEM OF ENSURING THE COMPETITIVENESS OF DIGITAL BRANDS
DOI:
https://doi.org/10.32782/city-development.2026.2-12Keywords:
social listening, competitiveness, brand, digital brand, Big Data, NLP, consumer experience, digital marketing, marketing insightsAbstract
The article examines the role of social listening as a strategic instrument for enhancing brand competitiveness in the digital environment. Under the conditions of Marketing 5.0, social listening is becoming a strategic tool that enables companies to transform unstructured social media data into valuable managerial insights. The purpose of the research is to systematize theoretical approaches to the interpretation of social listening, identify its strategic role in ensuring digital brand competitiveness, and analyze the technological foundations and limitations of its implementation. The study applies methods of comparative analysis, synthesis, systematization, generalization, and conceptual modeling. The evolution of approaches to social media monitoring is analysed, and the main directions of its interpretation are identified: the platform-communicative, the technological, and the managerial. Based on the analysis of existing concepts, social listening is defined as an intelligent marketing strategy focused on continuous automated monitoring and cognitive interpretation of textual and visual digital content for identifying consumer insights, forecasting market trends, and managing brand reputation. The study demonstrates that social listening contributes to digital brand competitiveness through three strategic vectors: identifying critical customer experience issues, analyzing authentic user-generated content, and supporting proactive decision-making based on trend prediction. The mechanisms of transforming unstructured data into insights are revealed, which ensures the transition from a reactive to a proactive model of brand management. Modern tools include natural language processing (NLP) and computer vision technologies, as well as the use of analytical platforms such as YouScan for visual and text analytics. Сonsiderable attention is paid to the ethical aspects of applying AI analytics, including compliance with data privacy requirements (GDPR) and the problem of result distortion caused by the influence of the “vocal minority”. The expediency of applying the Human-in-the-loop approach to improve the accuracy of data interpretation is substantiated. It is proved that the integration of social listening into R&D processes contributes to identifying consumer needs and engaging them in the co-creation of an innovative value proposition. Future research should focus on the integration of advanced artificial intelligence models, predictive analytics, and human-in-the-loop approaches to improve the accuracy and strategic value of social listening in digital brand management.
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YouScan. Available at: https://youscan.io/
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