Displaying data representing two different concepts in the same visualization can be difficult. A bubble matrix proves to be a helpful tool when confronted with this challenge.
In this instance, a university was interested in understanding their community’s level of engagement with the campus and how they could potentially boost engagement. The Applied Research Center assisted with this Community Engagement Project and conducted a survey relevant to the university’s engagement questions. Community members were asked to determine how this university could better engage with the people living in surrounding area. Survey respondents were asked to indicate their awareness of the different events hosted by the university, as well as their interest level in those events. With this data, we could take the two binary variables (i.e., aware/unaware and interested/uninterested), and display how the two variables interacted in a four-quadrant bubble matrix.
All events appear in each of the four quadrants, with the size of each bubble corresponding with the relative number of people that expressed the interest rating in each respective quadrant. Because this visual type would quickly become cluttered if N values were included in the bubbles, it would be wise to include a frequency table to support reader understanding. By organizing the data in this way, we can see that cultural events are the most interesting event types among individuals aware of them. More importantly, it becomes apparent that people are unaware of academic events but are highly interested in them. This provides actionable data that can be used to direct efforts and resources toward marketing the events generating the most interest.