Creative economy and value creation through marketing analytics: new approaches and opportunities

Abstract

The scientific article aims to determine the impact of marketing analytics on the value-creation process in creative industries. The research includes analyzing the use of digital marketing analytics tools in value chain creation to increase the efficiency and competitiveness of the creative sectors of the economy and creative industries. The research process used general scientific methods of cognition, namely, analysis of literary sources to determine the main trends in the development of the creative economy, comparative analysis to evaluate the indicators of different countries, and the method of generalization and systematization to identify and arrange the critical aspects of the impact of marketing analytics on the value creation of companies in the creative economy. In addition, an expert survey was conducted to substantiate the necessity and prospects of developing marketing analytics in the value chain creation of creative industries, which forms the basis for calculating the weighted average expert evaluations by SWOT analysis categories and correlation TOWS analysis conducted in the statistical analysis program JASP (Classical Correlation tool). Also, the Six Thinking Hats Technique was applied within the research, allowing for the systematization of modern theoretical and practical studies of scientists on applying marketing analytics in creative industries. The research results obtained by the SWOT analysis method indicate a high potential for technological transformation in the development of marketing analytics in the value chain creation of creative industries. The correlation TOWS analysis confirmed significant relationships between the effectiveness of extensive data analysis and the latest marketing analytics tools (r = 0.41, p = 0.02), the individualization of marketing strategies and the growth in demand for personalized products (r = 0.42, p = 0.02), as well as between the effectiveness of data analysis and the costs of integrating tools (r = -0.36, p = 0.04).