App Analytics and the Questions They Answer
Mobile technology has developed rapidly over the last few years. Almost everyone you know has a smartphone. You might even be reading this article on a smartphone.
Summer of Research
Project by Tuan Dung Ngo, AUT, supervised by Associate Professor Robyn Whittaker (University of Auckland and Waitemata DHB)
- Download/installation numbers
- Active users
- Crash rate
- Number of sessions and session length
- Heat maps (what parts of the app are being used the most)
There are many vendors of app analytics software that supply the above information (and much more) to app developers. Some of the most well-known solutions are Google Analytics, Yahoo’s Flurry Analytics, Fabric Analytics and Countly Analytics.
Tuan Dung Ngo decided to see whether there would be any benefit in applying app analytics to health apps to help advise clinicians. Mobile applications developed for healthcare purposes come under the umbrella of “mHealth”. This includes apps like calorie counters and fitness trackers. Many of these apps exist already but are often underutilised. Finding out whether healthcare providers are interested in app analytics could lead to more useful health apps for patients, and a more efficient healthcare system in general.
Orion Health gave Tuan access to anonymous, historical data from its own health and fitness app, “Rio Active,” to assist in his research. He analysed metrics such as app installations, usage patterns, active users and crashes. The reports generated from his analysis were intended to serve as examples and help in the next stage of his project.
Tuan then interviewed several clinicians and researchers to find out what they thought about app analytics, and whether it could benefit their work. While the participants ranked the importance of each tracking metric differently depending on their specific areas of work, they all agreed that app analytics has an important role in improving the user experience and helping determine how to make mHealth more successful.
The benefit of app analytics software comes in its customisability. You can set custom tracking parameters to analyse anything you might want to know about how the app is being used. This is especially useful in the health sector, as different organisations, app developers and even specific staff within these companies, will all have very different needs. A developer will want to know how many times their app is crashing, while a clinician will want to know what features of the app are being used by patients the most. If certain metrics aren’t available by default, these can be customised. This sort of information could also be used to tailor mHealth apps for certain demographics, or even individuals. Knowing exactly how users are interacting with mHealth software is another step towards precise medicine, and developing specific healthcare solutions for individual patients.
Tuan Dung Ngo is among a group of students who took part in the summer of research programme funded by Precision Driven Health. While at an elementary stage and considered to be a ‘proof of concept’, these summer projects offer fresh insights into what the world of healthcare will look like when precision medicine is fully implemented.