Designing Freemium: Balancing Growth and Monetization Strategies

Freemium (free + premium) has become the dominant business model among technology start-ups for its ability to acquire and monetize a large install-base with limited marketing resources. Freemium is a hybrid strategy where a firm offers both a perpetually free but limited version of their service, and a premium version with enhanced features that require a fee. Firms typically regard the referrals rewarded with free product as a promotional tool, even though it is linked to product strategy, leading to questions of interest to marketers. We develop an empirical microfoundations-based framework to understand dynamics of consumer behavior of plan choice, usage, and referral in the freemium setting and apply it to a novel panel data set from a leading cloud-based storage service. Using Bayesian methodology, we estimate the structural model and perform counterfactual analysis. We characterize the interplay between the cannibalization effects of the free product as well as the referral program, and we quantitatively investigate the tradeoffs in acquiring versus converting customers to the premium product – computing the acquisition benefits and cannibalization potential of the referral program.