Why data matters - and what we should be doing differently
A version of this article appeared in the FREE version of PULSE by Wareable. Subscribe here to get it to your inbox.
Sleep tracking is a core element of every wearable experience – and most top-class devices base their entire experience around it.
Oura is a sleep-tracking ring first and foremost, with its other health features built around that core feature.
Whoop is the same, and we’ve seen Garmin lean heavily into sleep features this year. In short: sleep sells.
It’s frustrating that sleep features have become an ever-increasing array of data points, not features or systems designed to help the user achieve better sleep.
This was a topic in last month’s epic podcast with James Hewitt, about how wearables can help us realize our potential. We discussed the pitfalls of sleep tracking – and I experienced a perfect example this week.
Data discrepancies
It may be controversial, but the area that I feel wearables get wrong about sleep is the focus on sleep staging.
As Human Performance Coach James Hewitt told me on the PULSE by Wareable podcast, wearables excel at two-stage sleep monitoring (when we sleep and wake). But there’s no evidence that tracking sleep cycles (deep/REM/light) is accurate.
I experienced that firsthand this week. Below you’ll see sets of data from Oura and Whoop from the same night.
“In the data, Whoop (left) tracks 2 hours and 45 minutes of REM sleep. Oura (right) tracks just 45 minutes. One is classified as unusually high – and the other is unusually low. One of these devices is wrong – but both are likely wide of the mark.
And why does it matter? As discussed in our podcast episode, James Hewitt points out that studies have shown that if a wearable shows us data that indicates low REM sleep, or any metric for that matter, we will perform accordingly.
“Perceptions of how we sleep affect our performance. Deception studies have shown that if you tell someone they’ve slept less, they perform as such,” said Hewitt.
“If you tell someone they had poor REM sleep, they will also experience a drop in their performance. So presenting data isn’t neutral – it’s a loaded experience that can change user behavior. Brands should consider whether day-level data is appropriate for a user – and encourage reflection on longer-term trends,” he said.
So disseminating data like this is not a neutral expression. The data is loaded – and wearable companies need to be more careful about how that is conveyed to users, especially when it might not be correct.
Making sleep tracking more useful
If you want to get more deep sleep, the main tool at your disposal is to sleep longer. But improving sleep conditions, such as better bedtime consistency and sleep hygiene, is also hugely important.
Wearables often focus on these elements, but these metrics are usually secondary to producing large amounts of sleep data.
A case in point is the new Huawei Watch Fit 3, which is a decent budget smartwatch. To bolster its credentials as a sleep tracker, it displays a huge array of data (see below). But is it useful to the user?
The Apple Watch was frustratingly close to making this connection. When it launched sleep tracking in watchOS 7, sleep stage data wasn’t included. It’s one of the few devices to display sleep consistency prominently on the watch itself.
So it was disappointing that Apple bowed to its focus groups and incorporated sleep stage data into the analysis, rather than expanding on its ideas around consistency and habit-building.”
In my podcast chat with Oura’s Holly Shelton, we talked about the potential of wearables leveraging the smartphone to consider environmental factors. Our wearables are increasingly obsessed with taking our temperature, but not that of the world around us. Likewise, ambient light sensors on smartphones have the potential to provide actionable suggestions about our sleep environment.
While I’ve criticised Whoop a little, its new Plans are an excellent nudge to build better sleep habits – such as taking a hot shower before bed or cutting out screen time.
I’m sure that most brands would argue that users want these features – and data sells wearables. But if that data comes at the expense of helping people get better sleep, or even subconsciously causing lower performance or anxiety because of inaccurate data, then we should demand better.