The biggest UX mistake in Digital Health
An efficacious mobile application is characterized by its ease of understanding, swift onboarding process, and its ability to deliver consistent value in an engaging manner. In other words, without demanding significant effort from the user, the application should be able to consistently deliver the expected value.
This topic is covered from a behavioral science and psychology perspective in our article on the Fogg Behavioral Model.
The mobile application industry, especially within the health and wellbeing sector, is abundant with products that struggle to attract and retain users due to their inability to meet the aforementioned criteria. Commonly, these applications offer an enticing value proposition, but require the user to contribute excessive effort within the app to reap the expected benefits.
It's important to note that the "value" of an app is highly subjective and depends largely on the user's perception rather than the opinions of the creating company. Generally, the more effort a user needs to exert to obtain the expected value - be it during initial sign-up or recurring usage - the lower the perceived value of the application will be.
Mobile applications often demand effort from their users in the form of data input, requesting the user to provide information so that the app can deliver value in its various forms such as interventions, recommendations, or education. Despite the promise of benefits, users can become weary of consistently providing or inputting information, leading to a decrease in perceived value, and subsequently, lower retention and engagement rates.
Two exemplary digital health applications that have successfully minimized user effort are Fitbit and MyFitnessPal. Initially, both applications placed considerable data input demands on their users - the more information a user provided, the more they received in return. However, over time, both applications began to harness technology and data tracking to automatically monitor fitness, nutrition, and other factors. This evolution in their approach continues today, with both applications maintaining impressive user acquisition and retention metrics.
Digital health mobile apps that command the highest perceived value are those that require the least user inputs and demand minimal user effort.
The question then arises - how can health applications reduce user “work” in order to increase their perceived value? The solution often lies beyond the constraints of traditional app engineering methods.
Fitbit, for instance, utilized behavioral signals from their devices to transmit data that would ordinarily require manual entry, and MyFitnessPal employed barcode scanning technology to capture nutritional information from food labels, eliminating the need for users to manually search and store this data. Both applications leveraged innovative technology to address the issue of “user work”.
Emerging technologies such as AI and Machine Learning are now readily accessible to developers through easy-to-integrate APIs. Health data can be obtained through methods other than user-driven forms, thanks to open APIs provided by device manufacturers like Apple and Android. Consequently, there are fewer reasons to solicit data from users to deliver value, provided their permission is obtained.
Modern approaches to data sharing and privacy control, which place these aspects in the hands of the users, are becoming increasingly popular among contemporary app developers.
The concept of 'data without forms, and answers without questions' is a more feasible proposition than one might assume in the context of shaping the future of digital health.