Let’s begin with a confession: I’ve always felt unfit for fitness trackers and the apps that go with them.
If I go for a walk or a swim, I feel good enough about my accomplishment without measuring every step or stroke. If I get a burger from Carl’s Jr., I can safely assume my net calorie intake has spiked without logging the gruesome details in an app. As for sleep tracking, I’ve realized that ignorance is bliss, as it’s more demoralizing than useful to realize I should have caught some deeper Z’s.
To put it another way, my early adopter tendencies don’t extend to the fitness realm. And I’m not alone; a November 2013 survey by Nielsen found that among the 70% of people who had heard of wearable devices, only 15% actually owned one (with the majority being fitness bands or other health trackers). And even among those users, attrition is a problem.
But that could change as fitness hardware becomes more capable, and as fitness apps get smarter about the data they collect. Instead of expecting the obsession level of a born athlete–which I am certainly not–these apps are slowly figuring out how to be useful to the rest of us.
On the most basic level, fitness apps are starting to turn the data they’re collecting–in most cases, calories burned, foods consumed, and hours slept–into suggestions to help improve users’ behavior.
Jawbone’s new Up fitness trackers, for instance, include a “Smart Coach” that occasionally gives advice based on users’ behavior. If it sees that you’re taking a long time to fall asleep, it might suggest reading up on some meditation tips. That’s a simple scenario, but Smart Coach can also cross-reference different types of data, noticing how your diet affects movement levels, or how sleep patterns during the week can have ramifications on the weekend.
Smart Coach can then encourage users to tweak their behavior. In one example provided by Jawbone spokesman Jim Godfrey, Jawbone identified 40,000 users who weren’t meeting their sleep goals, and suggested that they go to bed by 10:30 that night. About a third of those users said they’d give it a shot, and on average they logged an extra 23 minutes of sleep.
“If you’ve got three children, 23 minutes is the difference between a good day and a bad day,” Godfrey says. “… We see through these nudges that we really impact behavior.”
Another company taking a similar approach is Fitbug, which last month announced a set of workout apps for iOS and Android, dubbed Kiqplans. Fitbug sees them as a modern version of the fitness videos you’d find in a grocery checkout line–one male-centric package promises to banish beer guts–as they’re able to factor in things like the user’s starting weight and weekly activity levels.
“The guiding principle that we really want to build into Kiqplan is that the programs are really effective, and really help people achieve goals that are important to them,” Fitbug CEO Paul Landau said in an interview.
Like Jawbone is doing with Smart Coach, Fitbug wants to start cross-referencing different types of data to make these plans more effective. In the future, someone who got a poor night’s sleep and regularly drinks two cups of coffee might get advice on whether a third cup is necessary to power through the next workout.
Providing real advice based on existing fitness data is a good first step, but it’s still of limited use if you’re not regularly exercising or keeping track of your meals. Things get much more interesting, however, as these apps start gathering more types of data. With increasingly sophisticated hardware, and with data clearinghouses like Apple’s HealthKit, it’s getting a lot easier to offer useful insights.
Last week, an iPhone app called Lark started taking advantage of HealthKit in a major way, pulling in data from over 50 other fitness apps. Lark’s main attraction is its artificial-intelligence assistant, which converses with users about their activity and how they’re feeling. While Lark’s HealthKit integration is largely limited to calorie burn and calorie intake for now, it could eventually factor in services that measure heart rate and blood pressure. Future versions of the app could even offer specific advice for people dealing with diabetes or hypertension.
“Basically, HealthKit is our playground,” Lark CEO Julia Hu says. “Everything that HealthKit is providing as an input source is so easy for us to tie into our AI engine.”
For Lark, tying in new types of data is simply a matter of bringing in more health experts and adding new types of conversations to the AI. The process of working with experts can still take a while–Lark has been consulting with a cardiac rehab specialist for nearly a year as it tries to incorporate heart rate data–but the actual programming can now be done in a matter of weeks. “It’s a very flexible system, and we’re starting to go and build on top of our current release,” Hu says.
Of course, collecting new types of data still requires advances in wearable hardware, but those are now falling into place as well. Round-the-clock heart rate monitors are starting to appear in fitness trackers and smartwatches, including the upcoming Jawbone Up3, Fitbit Charge HR, and Apple Watch. (Fitbit, notably, is not supporting HealthKit as it builds out its own roster of connected services.)
Beyond just measuring overall heart health, Jawbone says heart rate data can provide clues about stress, hydration, and energy levels. The company plans to tie this data into Smart Coach over the next year. “As we roll out those services, we’ll be able provide people with a much richer set of information, and a much bigger picture of their health than we’ve ever been able to do before,” Godfrey said.
That’s not even the extent of what wearables can collect. Both the Up3 and Microsoft’s Band can also measure skin temperature, and we’re starting to see devices that measure sun exposure, mood, and even the blue light from computer screens that keeps us awake.
Over the next couple of years, the race will be on to use this data in smarter ways. You could imagine an app like Kiqplan measuring stress to figure out the best time to encourage a workout. Jawbone already has some basic integration with Nest thermostats, and in the future it wouldn’t be hard to regulate home heating based on body temperature. Microsoft has even talked about mashing fitness and productivity data together to figure out what makes people perform better at work.
Those are the scenarios that excite me the most. Good health is about more than counting calories, and as fitness trackers learn to take more of our activity into account, they stand a better chance of appealing to people who don’t see the point in measuring every step.