Editor’s note: Kristin Cavallaro is knowledge and data analysis specialist at research firm SSI, Hartford, Conn.
Go, go gadget hat! Oh the days that I remember sitting on my grandmother’s carpet watching Inspector Gadget and thinking how cool it would be to have super glasses or stilts that come out of my shoes on command. It all seemed so futuristic to me back then. While we don’t have propellers popping out of our hats today, we do have wrist watches that can call home, measure our heart rate, pay for our coffee or give us directions … and still tell the time. There are even socks that are feeding back data on your foot position while you’re running which link directly to your smartphone or a T-shirt that will measure how many breaths you’ve taken.
While many of the wearable technology devices are still making their way into the mainstream consumer market, fitness trackers are an example of a growing wearable trend. In an SSI study on wearable devices we found that approximately 18 percent of the U.S. population currently owns a fitness tracker such as a Fitbit, Jawbone or Garmin (Figure 1). Of those that own a fitness tracker, approximately 59 percent own a Fitbit, with iFit and Samsung Gear Fit as the next most popular.
When asked what types of clothing or accessories they would consider purchasing if they contained a computer, 46 percent would consider purchasing glasses while 16 percent of participants are not interested in wearable computers, as shown in Figure 2.
As with many things in our everyday lives, these little pieces of wearable technology are collecting large amounts of data. In fact, the National Institutes for Health is reporting at least 299 clinical trial projects that have used wearable technology to track the behavior and activity of the participants. This may range from testing the number of steps taken by wounded veterans undergoing different treatments or measuring the heart rates of those taking a particular drug.
Passive data
Are you thinking about using wearable technology in your next research project? As passively collected data is of increasing interest to researchers, these are some considerations to keep in mind.
There is a myth that passively collected data is correct and free of errors. This is not always the case. Look at the image below. As far as Nike is concerned, I climbed 150 floors in one day. That’s a lot of stairs! What they do not realize is that in reality, I hiked up a mountain not up flights of stairs. Regardless, this does tell me (and Nike) that I had a great workout that day; only the specifics are fuzzy.
Another danger is in not understanding what is being measured. We asked participants if they found their behavior had changed since using their fitness tracker. An astounding 83 percent answered yes. As a researcher, this data is not projectable to people in general given that the people we are sampling are those that are using a product and have consciously changed their behavior as a result of using it.
What is missing?
With any big data or passively collected database the danger is that someone is being left out. Are people who exercise regularly but do not own a fitness tracker in a wearables study different from those who own a fitness tracker? The answer is that we don’t know by looking at the data.
Comparing answers from this study to data previously stored in our databases about these participants, we discovered that people who own a fitness tracker were 21 percent more likely to own their home and 44 percent more likely to have children in the household. We found no significant difference in how often someone who owns a fitness tracker drinks but what they drink is indeed very different. Those who own a fitness tracker and drink alcohol are 72 percent more likely to drink whiskey and over twice as likely to drink brandy as those who do not own one.
As with any source of passive data collection and/or big data source, researchers need to understand that they are collecting data on a group of people that share something. Whether it’s the specific grocery store they shop in, what app they have on their smartphone or whether they own a fitness tracker. The specifics of the group being analyzed may present bias in the sample based on its origin.
Lastly it is important to remember that passive data and big data will only get researchers so far. It will answer the what, when and where but it is the why that helps strengthen marketing campaigns. It’s the “why” that inspires new product design. The what, when and where are each pieces to build a solid foundation of data and research but it’s the why that drives innovation. The why can only be gathered by asking questions and listening to consumers.