ESG Factors in Digital Marketing for Small and Medium Grape Growing Enterprises

In this research, TF-IDF technique is employed on the dataset that is empirically constructed on the purpose of identifying the impact of ESG factors on marketing activities. Although keyword frequency-based research studies is not capable of being predictive and robust in an real experiment based framework, it is more robust for the impacts of customer engagement and sales growth on performance levels. The grounding for the research innovation can be explain with reference to the integrated combination of TF-IDF and regression analysis, and feature weight calculation methods with advanced statistical modeling so as to examine ESG impact, thereby improving the predictive accuracy of marketing performance models. At the same time, combining the advantages of content analysis and statistical regression, it effectively processes marketing content, extracts relevant ESG-related keywords from it, and achieves actionable insights. The partial inter-relationships between ESG keyword inclusion and variables related to marketing activities are also in the impact of sector-specific options and, especially, considering the potential endogeneity of marketing objectives. A consequence of such sectoral differences is that we cannot generalize estimated effect representatively, despite the fact that the findings increasingly prove a positive impact of ESG-focused marketing on results of business performance.