The Freemium Challenge
In the digital world nowadays, the use of the freemium business model has become the standard. From professional networks such as LinkedIn to streaming services such as Netflix, companies offer their basic services for free to customers to create the initial attraction, hoping that they will then choose to upgrade to have access to premium features (Anderson, 2009). This strategy is very successful at helping a company grow, but it doesn’t come without any obstacles. Companies that employ have to ask themselves: How do you balance attracting a large user base for free while actually generating revenue?
Social Referral Programs
A common tactic used by companies is social referral programs. More specifically, incentives, such as unlocking premium features, are offered to existing users to bring in new users to the platform (Schmitt et al., 2011). This way the company leverages the most valuable asset they have, their existing customer base, to exponentially grow and keep generating revenue. However, even though in theory this tactic is successful, recent research on a freemium dating platform show that this strategy does not come without risks (Belo & Li, 2022)
What Research Shows
The study by Belo and Li (2022) on a european dating platform that used the freemium model found that there is a clear and positive correlation between the referral requirement and a the financial performance of a firm. More specifically, when the number of referrals needed to unlock a premium feature increases, there was a significant increase in the total number of referrals but also the overall revenue of the company. This signals that the strategy is successful and that more aggressive referral requirements would directly lead to more users and more revenue.
The Trade-off
Nevertheless, the story does not end there, as the same research showed that there is a double-edged nature to this strategy. Even though the user bases of the platform were growing exponentially and revenues were increasing, signalling winning, the company was losing on another crucial part: user engagement. As the number of referrals increased, users took longer to unlock the premium features, which in turn reduced their social utility and their engagement with the application. Thus, as a result of this strategy the company was gaining new users at the cost of existing customer churn.
My Take
Whether or not as a company you want to engage in this trade-off should depend on your time horizon. If you are focused on boosting short-term revenues for a funding round or to become more profitable, tightening referral requirements could be the way to go. However, in the long term such a tactic will undermine retention and growth that’s based on word-of-mouth, which are critical for the success of the freemium business model (Oestreicher-Singer & Zalmanson, 2013).
A smarter approach would to tier the rewards, meaning referrals would unlock some premium features but not all, keeping top-tier ones pay-only, as the study suggests (Belo & Li, 2022). Another alternative is making incentives time-limited, so engagement would be restored once new users settle in.
Takeaway
Social Referral Programs are a powerful tool when it comes to growth, but the growth does not come for free. Raising the bar of referrals might lead to higher revenues today, but may discourage the community that fuels tomorrow’s growth. The best strategy likely lies in carefully navigating the freemium equation by finding balance and using both sides.
References
Anderson, C. (2009). Free: The future of a radical price. Hyperion.
Belo, R., & Li, T. (2022). Social referral programs for freemium platforms. Management Science, 68(12), 8933–8962. https://doi.org/10.1287/mnsc.2022.4301
Google. (2025). A symbolic image representing the trade-off between user engagement and revenue in a freemium business model, with a prominent balancing scale at its center. The scale has two pans. The left pan holds a large, gleaming dollar sign ($), stylized to look heavy, and is tilted slightly downwards. The right pan holds a simplified, generic person icon, also stylized to appear lighter, and is tilted slightly upwards. The pivot point of the scale is perfectly centered. The background is a gradient of muted blues and greens, suggesting a professional and analytical context. Subtle, almost transparent lines and bar graphs are faintly visible in the background, hinting at data and business metrics. The overall image has a clean, modern aesthetic with clear, crisp lines and soft shadows to give depth. [Generative AI image].
Oestreicher-Singer, G., & Zalmanson, L. (2013). Content or community? A digital business strategy for content providers in the social age. MIS Quarterly, 37(2), 591–616. https://doi.org/10.25300/MISQ/2013/37.2.09
Schmitt, P., Skiera, B., & Van den Bulte, C. (2011). Referral programs and customer value. Journal of Marketing, 75(1), 46–59. https://doi.org/10.1509/jmkg.75.1.46
