Health And (H)appiness: In Search Of The Right Business Model

The MySugr app was launched in 2012 to help diabetics manage their daily treatment routines. Five years later, this mobile health (mHealth) startup counted over a million users and was acquired by the Swiss multinational Roche to further growth. Sweet success!

But in the developing landscape of mHealth apps, MySugr is more the exception than the rule. Many health-centered mobile offerings are having a hard time finding a sustainable business model to keep going.

A report on how to finance mHealth apps — prepared by IESE’s Jaume Ribera with Gabriel Antoja and Javier Mur — sheds light on the most viable business models for each app type, moving beyond the basic subscription model to uncover other ways to generate income sustainably.

Getting the algorithm right

Go to the “Medical” or “Health and Fitness” categories on Google Play or Apple’s App Store and you see thousands of options available. Patients may get overwhelmed, and even healthcare professionals have a hard time finding quality apps that are easy to use and suited to their needs. Even so, some studies project the mHealth app sector will be worth more than $30 billion in 2020, with a compound annual growth rate (CAGR) of 15%.

Given this potential, the authors have developed a tool for recommending income-generating business models, based on a conceptual framework. The report also identifies key factors that either help or hinder app monetization strategies.

The conceptual framework takes into account both who pays for the app (eight main options) and the monetization method used (another eight options). As far as who pays, the categories are: patients, health professionals (including students), public and private healthcare providers, public and private insurers, industry suppliers and, finally, other companies outside the health sector (including travel and telecommunications companies, for example). The monetization categories are: pay per download, user subscriptions, platform subscriptions, pay for services, marketing/advertising, sponsorships, pay for results/outcomes, and selling user data to third parties.

As for the key factors affecting the viability of each model, the report describes 70 variables for apps grouped into five main areas: (1) problems to be solved, (2) functional characteristics, (3) technical characteristics, (4) expected impact and (5) operating environment (for example, taking into account the different rules about advertising prescription drugs in the United States and the EU).

By using this conceptual framework, the potential value of an app can be estimated for each actor, as well as some key factors to help capture this value.

App market overview

Analyzing hundreds of offerings, the report finds that pay per download and advertising are the two most common financing strategies thus far. In addition, platform subscriptions (in which a company pays for a volume of licenses to offer its users) is gaining popularity as a B2B2C solution. Platform subscriptions may work together with pay for results (e.g., measured increases in efficiency) and pay for services. Meanwhile, the other strategies seem to be underutilized, the authors find.

Overall, the report highlights 32 working models for financing mHealth apps — with 19 identified as the most common. These include subscriptions for professionals and sponsorship by suppliers in the health sector. The report also notes that an app’s best business model may involve combining various strategies to secure more than one source of income.

The report offers a number of recommendations to market participants. For example, apps that get a lot of use should consider prioritizing subscription and/or pay-for-results models. And developers should temper their expectations for profits while the market is still young and fragmented, with clients unaccustomed to opening their wallets.

Methodology, very briefly

The authors first conducted an analysis of the status of mHealth apps in Spain and internationally to understand the main challenges and current good practices. They then worked to develop their analytic model and algorithm for apt recommendations for financing. Finally, they looked to actual business cases to validate their model and recommendations. They also took into account the advice of outside experts, who were consulted for all three stages of the study.