A Portfolio Optimization Approach to Cloud Computing Revenue Management: Balancing Customer Value and Risk
Pavan Nithin Mullapudi · International Journal For Multidisciplinary Research · 2025
This paper proposes a novel framework for applying investment portfolio optimization principles to revenue management in cloud computing enterprises. Cloud service providers face increasing challenges in maximizing revenue while managing heterogeneous customer risks. By conceptualizing customer segments as investment assets with distinct risk-return profiles, cloud providers can optimize resource allocation and customer engagement strategies. This research develops a comprehensive methodology that adapts Modern Portfolio Theory (MPT) to cloud customer portfolio management, introducing metrics for customer lifetime value (expected return) and various risk factors including churn probability, usage volatility, and competitive displacement. The framework enables cloud providers to identify efficient frontiers of customer portfolios that maximize expected revenue for given risk levels. Theoretical application indicates that such portfolio optimization approaches can yield 15-20% improvements in risk-adjusted revenue compared to traditional sales and account management strategies. This work contributes to both academic literature and industry practice by bridging financial portfolio theory and cloud computing revenue management.