Wellness Wearables Battleground Shifts From Hardware To Mobile Moments Enabled By Ecosystems
One of my first mobile moments this morning was a text from my husband on WeChat announcing that he had a Lark sleep quality rating of 9.4. We’ve become competitive sleepers. The Lark is a wearable device worn on the wrist at night to track the quality (e.g., number of times awake) and length of sleep. Activating the device requires you to set an alarm (and lets me know how few hours I have to sleep). The device wakes you by vibrating on your wrist. Disarming it in the morning includes journaling information on how you feel and what occurred that may have helped you to sleep well or disrupted your sleep.
While I love this device, in April Lark announced it will discontinue making hardware, but support existing units. It’s retained hardware staff to continue to understand how to make the most of data collected from sensors on the phones. Similarly, Nike didn’t announce it was discontinuing the FuelBand, but there were rumors it had laid off its hardware team.
Why these shifts?
These devices and apps are creating mobile moments by sharing basic data, a concept outlined in our new book, The Mobile Mind Shift. But, the excitement of reaching milestones of 5,000 or 10,000 steps a day or shifting your sleep behavior quickly fades once consumers have a sense of what it takes to reach these goals. In fact, overtime data can even demotivate individuals.
In order to change consumer behavior in the long-term, these wearables must offer effective engagement mechanisms that create relevant mobile moments that change over time with consumer needs. To succeed requires:
- Access to the data, but not owning or generating the data necessarily. Lark doesn’t need the hardware and dedicated readings to be effective. The detailed data is a nice to have, but expensive to obtain without scale. They engage consumers in what Forrester refers to as product use mobile moments through self-reporting each morning as well as ongoing coaching mobile moments throughout the day. Nearly two thirds of those who use their coaching service are still engaged and improving their sleep after 10 months. In comparison three quarters of those who don’t use coaching stop engaging after one month. Their internal team continues to learn and understand how to get the most from sensors on the phone as well as what is available in the health clouds to improve engagement tactics and results.
- Partner ecosystem and consumer permission to aggregate and use data. Improving the sophistication of insights will rely on aggregated data possible through API’s and consumer permission. Jawbone UP, for example, started out as a stand-alone device generating data, ingesting the data and displaying it in the app along with insights. Their service has since evolved to include a broad ecosystem of partners (e.g., Automatic, Whistle, MyRunKeeper, MyFitnessPal, Withings, etc.). This allows Jawbone first to create more sophisticated insights because they have a bigger picture perspective. It also allows them to create more personal (product use) mobile moments to engage their users. Some may have fitness goals while others may have weight or sleep goals. Engagement is also key – those users who engage at least 20 times each week take 25% more steps daily and sleep 23 more minutes each night. Apple, Samsung and Google are all helping to move the needle here with their cloud storage and development tools.
- Smart data scientists (and machine learning) to generate insights. Insights are key as catalysts to creating and winning in mobile moments. First, apps must be instrumented with analytics to collect data and generate insights. The type of insights generated from raw sensor data doesn’t tend to come in an off-the-shelf package – it is derived by teams of smart data scientists and those with specialties in machine learning. Traditional mobile analytics can tie in-app engagement to results. Interpreting data, however, in isolation or aggregate from a shared cloud source requires a smart team. Testing (e.g., A/B testing) through analytics is necessary to improve effectiveness in engaging consumers at the right mobile moments.
The combination of these elements enables effective mobile engagement in terms of creating mobile moments and serving consumers in those moments. To learn more, grab a copy of The Mobile Mind Shift here.