From fund managers, to local health and data enthusiasts, to random pedestrians downtown, we gathered data from a collage of viewpoints. We used every trick in the book (and learned some new ones) to discover our new direction.
I had to be able to react to events as they developed. Sometimes I would have a quick warning that an ideal candidate would be at the accelerator in five to ten minutes. And we’d have a small window (another 5-10 minutes) to talk to her before the scheduled meeting.
In response to this extemporaneous environment, I began creating user test kits. These had to be quick to make, quick to deploy, and easy to toss aside later. As the questions and the incoming data changed, I needed to make new supplies or new questions (or both) each day. We talked with dozens of people each day.
Everything I made while we were pivoting was built to be destroyed. And it showed in the materials–which was a good thing. Since the people we interviewed knew we were at the bottom of the ground floor with our idea–and that was reinforced visually through our materials–they thought more freely and openly about things than I’d ever seen before.
The ability to play on the interviewee’s ideas was key. For the more inspired interviews where we had time (and someone to take notes), I would create paper prototypes on the spot to clarify and test concepts.
We started finding traction at the intersection of personal health and the quantified self. With all of the new data points appearing every day, what better time and place to connect those dots to health than at a Nike-sponsored accelerator? With the general idea settled (improving health via analysis of users’ activities), it was time to solidify everything we knew about our prospective users.
By the end of the accelerator, a product vision was coalescing. I created the mockups to help us clarify questions for ourselves, as well as explain the product to outsiders.
One of the key issues we faced out of the gates was the fact that none of us were “data guys.” I had received minors in Mathematics and Computer Science. This hypothetically made me the closest thing we had to a data scientist (a sad statement for such a data-heavy company). That could be remedied by bringing someone else on board; however, that act would also compound financial and other issues. Decisions had to be made.
From my perspective, there were competing ideas for the future of the company, and mine were not winning the day. Furthermore, even with the minimalist “salaries” we were paying ourselves (I made more as a teaching assistant), our runway was burning up before our eyes. Is this still the company that I want to dedicate myself to? How can we all stay and still afford everything we need to survive? What do I really want to do? Where can I be of most use? Least of a burden?
After some meditation, the answer was clear to me. I still hesitated, but eventually resigned from NextStep. What did I leave NextStep to do? I got an M.S. in Information Science.