This paper presents a comprehensive design approach for interactive visual analytics frameworks aimed at enhancing the interpretation of institutional feedback and satisfaction survey data in higher education. Recognizing the limitations of traditional static reporting, the proposed framework emphasizes interactivity, usability, and the integration of both quantitative and qualitative data to support timely, evidence-based decision-making by academic leadership. Grounded in established principles of visual analytics and decision support, the framework addresses key design considerations including user roles, data diversity, and system architecture. Visualization strategies such as diverging bar charts, heatmaps, and sentiment overlays are recommended to maximize interpretability and actionability. The paper also critically examines implementation challenges related to data quality, user engagement, and ethical concerns surrounding privacy and anonymity. Concluding with reflections on design implications and future development opportunities, this work advocates for adaptable, user-centered solutions that empower higher education leaders to leverage feedback data effectively for institutional improvement and governance.