The bullet chart is a fantastic visualization tool for researchers and data nerds. It’s a great option when you are trying to show a lot of information in a small space. Created by Stephen Few, it was designed to more efficiently display information at a glance, and also lends itself to stacking which helps when we are comparing multiple measures at once.
There are 3 core components to a bullet chart. The primary value, the qualitative range in which that value sits, and the target that shows where this value should be, or was in the past.
Research Application: Tracking Data
In the market research world, the bullet chart is a great option for Loyalty, Reputation, and all types of Tracking studies. With these time sensitive studies, we we are often comparing regions, brands, segments across quantitative measures that need to be understood in a more qualitative range. Bullet charts allow us to display this information all in a single view.
For example, in a reputation study, we may have a core reputation score of 70, but is 70 good or bad? And, what if 70 is good in Canada, but terrible in Japan? What if we also need to know how this score compares to our performance last quarter? The bullet chart can solve these challenges!
In the above example, we can quickly see that our primary value of reputation varies by market, but so does our range. The bullet chart helps us see that our score in Africa is dipping into a concerning zone, even though this level might not be too concerning especially if it were in Asia Pacific.
If you enjoy tossing conventions out the window, try plotting the information in the round, or adding another dimension. Once you have the fundamentals of a bullet chart in mind (primary value + qualitative range + target), the sky is the limit!
Though you may sacrifice some efficiency in understanding, I guarantee you will have some fun experimenting along the way!