To explore how a small social enterprise in the edtech sector might visualize their user data through a dashboard, I employed a range of UX research and ideation methods including: competitive analysis, internal UX auditing, sketching, user scenarios, clickable prototypes, and finally, collaborative brainstorming.
I began my research with a competitive analysis of other edtech companies that offered data visualization features. By providing both a high level summary and specific details into each of the three companies I analyzed, I helped establish expectations for what capabilities my stakeholders were interested in exploring further.
Once we had a shared vocabulary for the types of capabilities a dashboard might include, I broadened the scope of my competitive analysis to include other data visualization platforms outside of the edtech space. This enabled me to map out a wider range of possible dashboard capabilities and ultimately expand our realm of inspiration before moving into ideation.
Before diving into brainstorming, however, it was important not just to cast a wide net of inspiration, but also to come to a shared understanding of possible internal capabilities. To do so, I conducted a thorough internal audit of current internal data sources. Using these internal data sources as a baseline, I experimented with different mapping techniques to see how these data sources correlated with competitor data visualizations.
Once I had a mutual understanding with my stakeholders of what we were inspired by, what our current data sources were, and how this data might map to various visualizations, it was time to ideate on what these visualizations might show and how. Based on the research done to date, we agreed on five main dashboard design principles to guide the ideation process.
The dashboard should highlight:
To inform our decision on what visualizations we wanted to move into higher fidelity and how, I employed a range of user scenarios to explore different visualization locations, filtering options, and links to the dashboard. Ultimately, I arrived at the following global and individual views and recommendations.
To gain feedback on these recommendations, I facilitated an internal stakeholder workshop where participants both critiqued pre-defined mockups as well as generated new visualization ideas.
I digitized the ideas from the workshop into the mockups below. Two years later, the tech team is still using my research to guide decisions and, iteration by iteration, moving towards our co-created recommendations.