Helping unions manage data for more than four million members across North America is second nature for UnionWare. But for their flagship product to fit seamlessly into their users’ workflows, finding and acting on data needs to be second nature for their users.
Search is one of UnionWare’s most powerful features—and one of its most complex. UnionWare recognized that creating a better experience in Search would create a better experience for every user.
Together with Quinn Keast through Caribou, I partnered with UnionWare to discover how Search fit into their users’ workflow and uncover the opportunities for the biggest impact in creating a better user experience.
When we spoke to the product team at UnionWare, we heard that unions around the continent were using their product to manage their data—a lot of data. And when there’s data, there’s search.
The team knew the existing Search experience was a pain point for their users. Every day, users need to find and work with their data, and UnionWare wanted to make it easier to learn and use. To do that, they needed a partner to help them gain a better understanding of their users and how Search fit into their workflow.
Our challenge was to help the team build a shared understanding of the user journey and uncover specific opportunities for making a better Search experience.
Based on initial discussions with the UnionWare team, we identified several specific challenges and questions to get us started:
We needed to understand how UnionWare's users were working today: what problems were they running into? What challenges were they facing? It was clear that the UnionWare team had a strong intuition, but needed to build out their understanding by hearing from real users.
Understanding our users means building a deep sense of empathy. To get started, we met with a training specialist from the product team and got our first experience with Search from the perspective of a new user.
UnionWare holds an annual conference for its users to learn from hands-on training sessions, connect with the product team in a state of the union, and participate in shaping the future of their products. We joined UW Summit to hold a micro journey mapping workshop with real users. How did they recall their activities while getting their job done? When did Search enter the picture? Where were the key emotional moments? The conversations that grew out of the workshop—and the Summit—were invaluable.
We created an insights framework for capturing and interpreting insights in one place, and shared it with the whole product team.
While we were learning about our users, we wanted to get a better sense of the product, challenges, and capabilities directly from the product team. We held a series of stakeholder interviews with every level of the organization, from customer support to the CEO, to understand their role and the context they could provide.
A journey mapping workshop helped a cross-disciplinary product team work through a complex user journey from beginning to end for the first time. What were the pain points that we knew existed today? What were the key emotional moments, from the perspective of the product team? Where were the gaps in our knowledge?
We had questions. To answer them, we reached out and sat down with real users in a series of one-on-one user interviews to observe how they performed searches and hear their stories. We asked broad questions to set the stage and then drilled down to get a better understanding of how they use Search.
The user research we conducted through this project lead to the delivery of a findings and recommendations document that:
We discovered that all users went through a natural process of trial and error while making a search. In the existing experience, users tried to “get it right” the first time. Minimizing the tangible impact of each iteration in this process was an opportunity for real positive impact on the Search experience.
A powerful search doesn’t need to have a complex interface. Less complexity means less mental overload for users trying to get their job done.
We discovered a clear divide between two types of users: those who treat Search as if they were solving a problem, and those who treat Search as if they were answering a question. This was an opportunity to create, implement, and teach a shared mental model around building a search.