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Is There Zen in Freemium?

person in meditation pose

Is There Zen in Freemium?

In search of strategies to boost revenue and premium subscriptions in freemium communities.

The “freemium” business model is widely used by the makers of software services, mobile apps, games, and online social communities. From Dropbox to Angry Birds, Spotify to LinkedIn, freemium underlies many digital-age products. But companies using the model grapple with an inherent challenge: how do you make money on something you’re giving away for free?

The Study

Freemium services offer free and premium (i.e., paid subscription) versions of a product simultaneously. Free versions may attract users and generate some revenue, often through advertising; however, premium subscriptions are much more valuable and therefore critical to the long-term viability of freemium businesses. In this study, Ravi Bapna, Jui Ramaprasad, and Akhmed Umyarov explore the relationship between payment and social engagement in an effort to identify mechanisms and strategies that can increase premium subscriptions.

The authors of this study build on previous work that showed how social participation and peer influence drive free users to convert to premium subscribers. In addition they cite marketing research that links payment to product performance. Using the online music-listening community Last.fm, the researchers investigated whether paying for a premium subscription increases social participation in the community. They find that it does, suggesting a “virtuous cycle” between payment and participation.

Graphic of the virtuous cycle tracking engagement, influence, and revenue in freemium communities.

 

Impact

Mechanisms of payment, participation, and influence within an online social community are powerful tools if correctly understood. Companies can use such knowledge to design more effective product features, marketing strategies, and incentive programs based on empirical evidence of cause and effect, and not correlation. Evidence from studies like this one can help generate revenues, ensure an online community’s health, and ultimately fortify the future viability of the business.

 

Methods

Look-ahead propensity score matching, random effects

Tools

SAS, R

Co-authors

Jui Ramaprasad