KEY ASPECTS OF APPLYING CORRELATION-REGRESSION ANALYSIS FOR MARKETING RESEARCH
Journal: International scientific journal "Internauka." Series: "Economic Sciences" (Vol.1, No. 87)Publication Date: 2024-07-31
Authors : Suvorova Svitlana Rassokha Inna Naboka Ruslan;
Page : 178-184
Keywords : statistical analysis; mathematical model; linear multiple regression; marketing strategies; economic conditions; predictors; marketing research;
Abstract
Introduction. The article is devoted to topical issues of the application of correlation and regression analysis in the field of marketing. In modern conditions of dynamic development of market relations and growing competition, marketing research is becoming an integral part of the successful activity of enterprises. Correlation-regression analysis allows you to identify hidden patterns and trends, which helps to optimize marketing strategies, increase the effectiveness of advertising campaigns, and improve consumer satisfaction. Research and implementation of this method in the practice of marketing research not only enables companies to adapt to changes in the market but also reassures them of their ability to make more accurate management decisions, ensuring their competitiveness and sustainable development. Purpose. The work aims to evaluate this method's effectiveness in determining marketing trends and making informed decisions. Materials and methods. The article examines correlation and regression analysis methods used in marketing to assess the relationships between various marketing variables and their impact on marketing campaign results. Results. The critical aspects of applying correlation-regression analysis for marketing research are studied. Within the framework of the study, the main problems of using correlation and regression analysis methods in marketing were identified, current trends and innovations in their application were evaluated, and potential directions for further development were identified. Using a classical linear multiple regression model, the authors investigated the strong linear relationship between the variables. This was confirmed by the high values of the coefficient of multiple correlation (R = 0.973) and the coefficient of determination (R² = 0.947). The adjusted R² value (0.761) was also analyzed, demonstrating the model's generalizability from the sample to the target population. An empirical study's results were given, demonstrating the practical value of these methods for evaluating the effectiveness of marketing activities. Prospects. The obtained results can be used by marketers and researchers to obtain new insights and to develop analytical approaches. Your role in further developing the field is crucial, and your contributions will be integral to the process.
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