An effective mobile app is easy to understand, quick to onboard, and fun to use. Put another way, with little to no work from the user, the app delivers the value one expects time and time again.

The mobile app landscape is littered with health and wellbeing products failing to gain and retain users because they miss one or more of the aforementioned criteria above. Often, the value proposition is compelling, but the user is required to perform too much (and sometimes anything more than nothing is too much) work within the app to receive the anticipated value.

Given that “value” is subjective, it is the user’s perception, not the creating company’s, that is the most important opinion when assessing value. As a general rule of thumb, the more work a user needs to do to receive expected value, whether it is during initial sign up or on an ongoing basis, the lower the perceived value of that app will be.

One of the ways that mobile apps require work from their users is by prompting them to enter data, to tell the app something, so that the app can return the value in whatever form that takes (e.g. interventions, recommendations, education). Despite knowing a benefit awaits them, users are tired of being asked information or inputting information, so the perceived value falls, with retention and engagement soon following.

Two examples of digital health apps that reduce the work their users do are Fitbit and MyFitnessPal. At the time of their inceptions, both apps placed heavy burdens on their users to input data. The more a user gave, the more they received. Over time, the apps began to leverage technology and data to track fitness, nutrition, and other elements automatically. This shift continues today with both apps continuing to enjoy healthy acquisition and retention metrics.

Digital health mobile apps with the highest perceived value require the fewest user inputs and ask for the least amount of user effort.

How can health apps reduce user “work” so their perceived value increases? The solution is often outside of the bounds of what we consider standard procedure while engineering apps.

Fitbit used behavioral signals from their devices to transmit data that would otherwise be manually entered into forms, and MyFitnessPal utilized barcode scanning technology to capture nutrition information from food labels so the user didn’t have to search and then store this information manually. Both apps turned to new technology (at the time) in order to solve the “user work” problem.

New technologies like AI/ML are now accessible to most developers through simple to integrate API’s and health data can be captured by means other than user-driven forms by readily available open API’s from device manufacturers such as Apple or Android. There is swiftly becoming less reasons to ask users for the data needed to deliver value to them, so long as their permission is granted to capture it, and thanks to modern approaches to putting data sharing and privacy control in the hands of users approaches like this are becoming more frequently used by modern app developers.

Data without forms, and answers without questions is an easier proposition than one would think when it comes to creating the future of 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.

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”.