Demystifying Heat Map Visualizations

Since heat maps can be very visually appealing

, we often get questions from customers about how to best use them in custom dashboards and reports.

At their most basic, heat maps are used to quickly (and visually) identify outliers in your data. Instead of having to navigate spreadsheet-like columns of numbers, heat maps let you quickly compare data values with two distinct visual cues: color and size.

Here's a quick example of a standard heat map view looking at just the "size":

Sales Pipeline Data by Sales Rep

In the above heat map, we're comparing sales pipeline data on a single visual cue: the size of box. The larger the box, the bigger the pipeline and the less cause for alarm for our sales manager. It's pretty easy to tell that Anna and Larry are the top performers based on this chart.

Now let's introduce our second visual cue: color.

Sales Pipeline Data by Sales Rep

Color=Average Deal Size, Size=Total Amount

The color is being used to represent each person's average deal size. The color gradient lets us quickly identify how far from the median value a particular metric happens to be The darker the red, the higher the number while green, in this case, means lower numbers.

Using these two visual cues, we can quickly identify outliers that we wouldn't have found otherwise. Take a look at the boxes that are small, but also red. That means the salesperson is counting on a small number of deals to meet the sales goal and, if one deal drops off, there could be trouble. Knowing this data can help us to drive further actions, such as custom alerts, email notifications, or simply a greater awareness of the risk.

Heat maps with a twist.

While the box layout heat map is a great way to find our data outliers, sometimes it also helps to use heat map color comparison in a wider variety of outputs such as a geographic map. Take a look at this example:

Again, we're using two visual cues to build a quick comparison of the data: the color gradients (our number of deals) and the state or location on our map. These types of visuals are commonly referred to as choropleth maps. While not exactly the same as a heat map, the choropleth map allows you to visualize your data across a color spectrum to quickly identify the deviation from a median value within your data within a defined geographic boundary. This can be very useful for quickly comparing region or population data as another variable. Judging by this map, it seems we have a few states that are under performing (the ones in red). If we drill down into those state details, we may find additional information about what actions need to be taken to improve the performance.

Demystifying Heat Map Visualizations

By: David Abramson

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