Do people want personalized wearables?

After exploring and researching the wearable market during the last two weeks, we wanted to build a first, low fidelity experience prototype to determine if users actually have a need for our idea.

At first, however, we had to decide in which direction we wanted to go. The benchmarking and user-need finding had shown us three different fields:

1. Social features in fitness & health
2. Better data visualization and derivation of insights from collected data
3. Platform to aggregate data from different sources

In our interviews we heard a lot of people complaining about missing insights of their data.

What does it mean to walk 5000 steps per day? Is it good? Average?

This is, why we decided to try to come up with better ways of conveying valuable insights to users.

Brainstorming

How might we inform the user about his current fitness progress using tech?

In Design Thinking, brainstorming is about going crazy. No idea should be judged immediately. Even if it seems totally impossible or stupid it could inspire someone else in the team to come up with a better idea based on the crazy one. In the following, see some of our ideas:

• Personal Tamagotchi — A virtual animal that the user cares for and that dies if the user does not work out enough
• Electric Shocks — Give the user electric shocks if his fitness level drops
• Weekly Coach Reports — Every week a professional trainer calls the user to evaluate the users progress
• Gather & Include more data — Collect car usage, smart home data, etc. to get more insights about the user and consequently have a better understanding of his behavior

In conclusion, we came to the realization that basically all of our ideas aimed at a more personal experience for the user.

Prototyping

Therefore, we decided to try to prototype exactly this: a more personal wearable experience for the user. That prototype should answer some basic questions:

• Do people want personalized feedback?
• Would personalization actually increase the usage?

The following idea was to hand the users two different wearables. One would simulate a regular wearable and another one would get to know the user for a week, learn about his habits and hence present recommendations. Thus, we developed the following experience prototype process:

1. Survey the tester about his daily and weekly routines and sport activities
2. Give tester the first wearable and let him walk around the block simulating wearing the device for one week
3. Present the tester plots and statistics for the week and survey them about their thoughts and feelings about the data
4. Give tester a second wearable and let him walk around the block a second time to simulate wearing it for one week
5. Present the tester more personal feedback and recommendations based on his habits (use insights from 1. for that)

Testing

Subsequently, we tested our prototype with multiple testers and got the following insights:

• All of our testers said that they the raw data as presented from the first wearable is useless for them
• They think that the data has to be compared with other values (like other users, optimal values) and set into context to generate insights for them
• All of our testers liked the personalized experience more than the other one. They responded positively to recommendations (e.g. of other apps, of personal goals based on the learned behavior)
• One tester said that he would like to know the exact reasoning behind recommendations, in order to trust them
• Ideas from our testers: Integrate the user’s calendar into collected data to see explanations behind values (e.g. low step count for that day, because he had a lot of meetings), vouchers for sport equipment if it matches users behavior

Conclusion

We were happy with the results of our prototype and came to the conclusion that our testers liked a more personal experience. Moreover, it got clear to us that it is very important to not simply hand users raw data, because they cannot generate any value from that. A wearable which gets to know the user and becomes the user’s buddy by giving useful recommendations and tips could be a way to deepen the bond between device and user.