Modelling the Growth of OTT Platforms During Lockdown Using Constraint Programming: A Mathematical Approach

The COVID-19 pandemic led to a global lockdown, transforming consumer behavior and catalyzing a dramatic rise in Over-The-Top (OTT) media consumption. This paper presents a novel approach to modeling this growth using Constraint Programming (CP). By incorporating demand drivers (subscription cost, content volume, internet penetration), temporal constraints (lockdown phases), and budgetary limits (household income allocation), the model identifies optimal strategies for OTT adoption and platform content scheduling. A diffusion-based CP framework is used, highlighting how internal and external influences impacted subscription spikes. We also provide sensitivity and stability analyses to study the robustness of the model under policy or economic shifts.