From Growth to Monetization: Managing Freemium Services

Motivated by the recent rapid growths of freemium services, we study freemium service providers’ dynamic operating policies to maximize their lifetime profits. We adopt a hybrid of the Bass diffusion model and the replicator equation from evolutionary game theory to capture the user base growth, and model the provider’s dynamic decisions as an optimal control problem. We analyze two variants of the freemium business model inspired by two prominent examples, Dropbox and Spotify, which, respectively, adopt the monetization strategies of limiting features and advertising (and its removal). We establish the optimal dynamic operating policies for the Dropbox-inspired ad-free freemium model and the Spotify-inspired ad-supported freemium model and identify their distinctive operational characteristics: the optimal policies as well as the sustainability of the Dropbox model critically depend on the network effect among users, whereas the optimal policies of the Spotify model show that advertising could be a more effective monetization strategy than limiting features. The latter observation is confirmed in a general model allowing both monetization strategies where the optimal policies consistently adopt advertising without limiting features. We then show that the freemium model significantly outperforms the ad-supported free model in weak advertising markets and that offering multiple tiers of premium subscription is unnecessary and confirm our core insights’ robustness under a generalized network effect, customized advertisements, and liquidity constraints. Our study establishes the versatility and value of the freemium model to suit distinct needs of a service in different stages from growth to monetization, and provides guidelines for service providers adopting this business model.