With the rise of social media came the the need to analyize the billions of data points created each day. Each tweet, comment, and review contains valuable data for brands and researchers. Whereas other types of analytics rely on numbers, social media analytics is based heavily on understanding human-written content.
When I joined the Watson Analytics team I knew next to nothing about analytics. As with many projects the learning curve was steep but fascinating. I joined the project to redesign IBM’s Social Media Analytics product. The powerful back-end of the product was masked by the disjointed experience and complicated UI. I think the only people who knew how it all worked were the engineers who built it which made it a challenge for users.
I know what you're thinking. "Are those all the same product?" The answer is yes. That was one of the concerns we had as a UX team when kicking off this project.
Through interviews with 18 users conducted by a research team member, we uncovered a few main issues we needed to address.
As we learned more about the way the product is built and how to configure the most effective social media models, we created a list of feature requirements for whatever framework we were going to use for the redesign. This list was created through conversations with our product manager and the engineering team.
This is the last work I accomplished for the project before leaving IBM to become a UX designer for athenahealth. As you can see below, the team who continued the project did not drastically change anything when implementing and iterating on the designs.