The Brief: Use an existing dataset to define a problem and then provide a solution.

The Process: User Interface Design II Professor, Molly McClurg, suggested picking a dataset that was related to something we, as students, were passionate about. Animal welfare has been a topic that I have been concerned about ever since my family adopted our first cat decades ago. Today, I volunteer with the Austin Animal Center, Austin Pets Alive and Austin Humane Society.

During my preliminary research I found that Austin Animal Center keeps an active database of all pets found on the City of Austin’s Open Data Portal.

Using this data I was able to glean some insights into how people in Austin search for and report lost pets. I found common pain points were that current methods were not only time consuming and counter-intuitive, but they tended to be very inaccurate. Also, the current system didn’t address the emotions that end-users were experiencing. Anyone who has lost a pet understands the fear, anxiety and overall stress that encompasses that situation. From this data I was able to define the problem.

After establishing the problem the next step was to fully understand the users. I conducted user interviews and was able to understand their goals, problems and who they were. By understanding who the end-users are, I was able to create personas – one for a user who had lost a pet and another for a user that had found a pet. I ran these personas through journey maps to figure out where they ran into hurdles, which was incredibly insightful into how I could improve the overall process and help the users achieve their goals…

Introducing Sheltr, a web-based app that provides comfort to people who have recently lost their pets by providing a centralized, efficient and accessible database of lost and found pets.

Sheltr aims to reconnect users with their four-legged friends by streamlining the process. My goal was to implement common UI patterns to guide the user through the process step by step. Sheltr is successful by asking the right questions at the right time, and providing feedback in a timely fashion. This helps put the user at ease, and gives them hope during an otherwise nightmarish experience.

The Brief: How can we help young women stay safe while drinking?

The Process: The first step was to validate our concerns by conducting interviews with women about their drinking behaviors. With these interviews we developed a persona of our user, known as Shelby. We used that persona and the data from the interviews to develop a problem statement:

"Shelby needs a way to be safe when she drinks, a support network to help her manage her risky behavior, and a way to get home safely."

We then created an "as-is" journey map for Shelby. We ran her through the journey many times, noting key pain points. We developed these points into our hills. The hill represent the individual problems we want to solve for. 

From here we iterated and ideated until we came up with a prototype of an application, aptly named, Swerv! It's important to note that at every step of the way, we tested the app's functionality against our user persona. Always running Shelby through her journey. This is the crux of user-centered design. 

With Swerv, Shelby can now enjoy her night safely and stay connected to her support network, while still letting loose and having a good time. 

An InVision prototype of the app can be found here.