How Free Digital Products Grow

Gil Appel, Barak Libai, and Eitan Muller, 2015, 15-100

An intriguing development in the marketing landscape of recent years is the substantial increase in the quantity of digital products that are introduced to the market for free (using different business models to create profit following the free product). The free model has become ubiquitous across electronic platforms with app stores and large online sites offering a large variety of free products.

Recent reports highlight the omnipresence of the phenomenon: More than 90% of the downloaded smartphone applications in 2013 were free, with this percentage expected to continue rising in the near future. In established markets for digital products, a fierce battle is being waged among “freemium” and “premium” business models.

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How free digital products grow

The large scale introduction of free products raises the question of whether our knowledge of the dynamics of conventional product markets can be applied to these new phenomena. A fundamental question regards the pattern of growth for free products. Would it follow the growth pattern recognized for conventional non-free new products? Would the relatively riskless adoption and the ubiquity of offers change the pattern by which customers adopt such products?  These issues are essential for prediction, segmentation, and management in such markets. They are of interest also for marketers of traditionally non-digital goods that increasingly introduce free mobile applications and software that helps the brand in terms of promotions, service, and reputation.

Using a database that documents the life cycle of tens of thousands of digital products, authors Appel, Libai, and Muller provide first evidence that freeware’s growth pattern departs from the life cycle pattern observed for classic new products--the traditional bell-shaped growth with a cumulative “s-shaped” pattern. They show that freeware products may actually start their market presence with a drop in demand, and identify archetype growth patterns for such free products. They further show that the growth pattern strongly depends on the product’s popularity, where highly popular products (which are in fact a minority in the market) follow the bell-shaped growth, yet this tendency declines as popularity decreases. Finally the authors elaborate on how the nature of influence in such markets can explain the patterns observed.

These findings suggest that, when dealing with free digital products, managers may want to use caution in making predictions and marketing plans that are based on the conventional wisdom of traditional products. In particular, the tendency of past research to focus on popular products may bias our understanding of markets where many products are not superstars.

Gil Appel is a doctoral student in marketing at the Glazer Faculty of Business and Management, Ben-Gurion University of the Negev, Israel. Barak Libai is Professor of Marketing, Arison School of Business, Interdisciplinary Center, Herzliya, Israel. Eitan Muller is Professor of Marketing at the Stern School of Business, New York University and at the Arison School of Business, Interdisciplinary Center, Herzliya, Israel.

The authors would like to thank Zvi Gilula, Oded Netzer, Jacob Goldenberg and Gal Elidan for their advice and help during the research process.

Related links

Ten Million Readers Can’t Be Wrong!” or Can They? The Role of Information about Initial Adoption in New Product Trial
Coby Morvinski, and On Amir, and Eitan Muller (2014) [Report]

Targeting Revenue Leaders for a New Product
Michael Haenlein and Barak Libai (2013) [Report]

Innovation Diffusion and New Product Growth
Eitan Muller, Renana Peres, and Vijay Mahajan (2009) [Book]


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