When asked to list examples of traditional charts and graphs, most people will name bar, line or pie charts. Rarely do people list radar charts, histograms, or bubble charts, but these types of charts can be exceptionally useful when needing to visualize data with multiple variables. Dive in with us as we explore the bubble chart and how it can be used for qualitative and quantitative data visualization.
What is a bubble chart?
A bubble chart is a data visualization that is used to show the relationship between multiple data points – typically three, but sometimes four. The bubble chart is an extension of the scatter plot, which focuses on the representation of two variables. In a bubble chart, each circle (bubble) in the chart represents a data point that shows its position relative to the horizontal (x) and vertical (y) axes (as does a scatter plot), but the bubble chart goes further to include the area of the circle as a data point, which represents a third variable. An example can be seen below:
In the bubble chart above, we can compare the number of games won (x-axis) to the number of points a team has (y-axis), while looking at the respective team size (size of bubble). As is evidenced by this data, Team A, with the highest number of team members, won the least number of games and scored the fewest points, whereas Team F, with fewer team members won the most games.
Bubble charts require a minimum of three variables of data that can be used to determine the size of the bubble and its positioning on the corresponding axes. It is, however possible to add an additional variable to the chart by showing differences with the color of the bubble.
How do I use a bubble chart?
Now that we have a general understanding of bubble charts, we can look at use cases. Most individuals will use bubble charts for quantitative measurements, as seen in the example above. It is relatively easy to assign the size of a bubble to a quantitative value such as number of individuals, price, frequency of use, etc. Using bubble charts to visualize quantitative data is great because it allows for quick comparison of values.
However, what should you do when you want to use a bubble chart to visualize qualitative data? The simplest approach is to assign numerical values to your qualitative results; this is referred to as qualitative data coding. At HelloInfo we frequently use qualitative data coding to analyze information from qualitative sources such as interviews, open ended survey results, and focus groups.
An example of a bubble chart that analyzes qualitative data might be included in a product study investigating customer use of certain product features. The chart may investigate the following variables:
- Satisfaction level of a particular feature for those customers
- Amount a particular feature is used by the customer set
- Price of that feature
This chart would be informed by qualitative assessments of interview or survey results from customers on frequency of use, and their associated satisfaction level with it. It would also pull in quantitative insights from secondary research to obtain the pricing.
If we look specifically at one of the variables, satisfaction, we may ask in an interview “How happy are you with feature x?” The question is open-ended, leaving the opportunity for multiple answers which may look like:
- The feature is fine, but I wish it could do more.
- I’m unhappy, I am not able to do these specific things with it.
- I am extremely happy; it does everything I need.
- I am indifferent. I don’t use it at all.
While each answer is unique, we can codify the data, and determine an average satisfaction level with the feature, weighing each response based on the associated satisfaction level. We can then do the same to obtain quantitative values related to the amount of use of the features.
This bubble chart may end up looking something like the below, where each bubble represents a feature, and you can easily determine use, satisfaction, and price of that particular feature. When examining this chart, it is obvious that Feature 5, priced at $80, is highly used and sees high customer satisfaction.
Bubble chart best practices
When creating a bubble chart, the following best practices should be kept in mind:
- Limit the number of data points included: It is important to keep your chart readable by limiting the total data points, and if necessary, adjusting your analysis or looking for other chart types.
- Variable placement: The two most important variables should be placed on the x and y axes.
- Size bubbles proportionally: To avoid misrepresenting your data, make sure that you are sizing the bubbles on the chart in relation to one another.
- Represent negative values differently: Incorporating negative values can be useful when looking at qualitative data visualizations. While the bubbles cannot physically have negative space, they can be hollow, multi-colored or on a negative axis.
- Make sure the legend and all labels are visible: Clearly labeling all aspects of your bubble chart will ensure that individuals consuming the chart understand the information being presented.
At HelloInfo, we are experts at quantitative and qualitative data analysis and visualization, and our core competencies are executing the full cycle of conducting research, coding information, and using our data visualization skills to tell a story. If you are interested in learning more about how HelloInfo can help your company tell stories with data, schedule a call with us.