Digital Engagement in Higher Education: A Comparative Study of Social Media Marketing Strategies of Selected Pakistani Universities

Abstract

This research project investigates the digital marketing performance of Bahria University Islamabad (BUI) through a comprehensive benchmarking analysis against leading Pakistani higher education institutions. Recognizing the critical role social media platforms play in influencing student decision-making and shaping institutional reputation, the study evaluates BUI’s online engagement, content effectiveness, and competitive positioning using a structured, data-driven methodology. A mixed-method netnographic approach was employed, integrating quantitative metrics—such as engagement rate, share ratio, audience growth, and video performance—with qualitative insights derived from sentiment analysis and thematic review of audience interactions. A refined content taxonomy was developed and validated through pilot testing, achieving high inter-coder reliability and ensuring consistency in the classification of social media posts. The findings reveal that BUI significantly underperforms compared to competitors, particularly in engagement rate, content diversity, and video effectiveness. While the institution maintains a positive audience sentiment, interactions remain largely passive, highlighting limited resonance with target audiences. The research contributes both theoretically and practically by introducing a higher-education-specific social media taxonomy, developing a competitive KPI framework, and presenting a validated benchmarking model suitable for institutional adoption. A comprehensive deployment strategy was proposed, including short-, medium-, and long-term action plans focused on automation, platform diversification, predictive analytics, governance frameworks, and workforce upskilling. The study concludes that BUI must transition from intuition-based digital communication to systematic, insight-driven strategy to strengthen its digital presence and remain competitive. Limitations include platform scope restrictions, a six-month data window, and reliance on manual coding. Future research opportunities include linking social media performance to admissions outcomes, expanding benchmarking across cities, and integrating advanced AI-driven analytics.