Many professionals, including engineers, doctors, marketers, and researchers, utilize heat maps to visualize data sets and turn them into comprehensive, actionable takeaways. As part of our series on qualitative data visualization, dive in with us as we explore this interesting way to present information.
But what exactly is a heat map and how can it be utilized for your business needs?
What is a heat map?
A heat map, by definition, is a data visualization technique that shows the magnitude of a phenomenon as a color in two dimensions. Originally created as 2D displays of values in a matrix, heat maps date back to the 1870’s. Statistician Toussaint Loua used heat maps to visualize social statistics in Paris, via the shading of a square. Darker shaded grey squares indicated a higher value, while lighter squares a lesser one. In 1991 software designer, Cormac Kinney trademarked the term ‘heat map’ and described it as a “2D display depicting financial market information.” While both Loua and Kinney used and developed heat maps, the resulting data visualizations were not identical. Loua’s heat map within a two-dimensional matrix created what is known as a grid heat map, while Kinney trademarked spatial heat maps, which display the values of spatial phenomena casted over a map, as well as grid heat maps.
How can heat maps be utilized?
Spatial heat maps and grid heat maps can be used to display the same information in two different ways, however, each is better suited to a respective niche. Grid heat maps can only have two axis variables, which act as ranges, much like a bar chart or histogram. Each cell’s colour dictates its value within the heat map, with darker colours usually representing a higher value than lighter colours. When dealing with large data sets that only look at two variables such as rainfall per month, or product sales per quarter, grid heat maps can be a visualization tool that is easy to analyze. Within its respective niche, a grid heatmap provides a simple to understand informative display of information, that also allows for intuitive trendspotting and data analysis. When looking at information such as monthly rainfall it can be beneficial to researchers to be able to intuitively spot trends, and discrepancies in order to make quick decisions, or analyzations of the data presented.
Spatial heat maps do not have data constrained within a 2D matrix and can have their data cast over a map based on geographic locations. For example, if we want to create a population density map in the town we live in, we can create a bar graph with each district being represented by a respective bar. In this method a taller bar would indicate a higher density and a smaller bar a lower one. While this method works, if a third party were to view the bar graph, they would need to reference it against a map in order to have a complete understanding of the data. Referencing a spatial heat map would allow us to overlay the population density directly on the map of where we live, rather than having the density siloed in a separate chart. With this visualization, denser areas would be saturated with more data points creating a darker or warmer shade. This would show not only the districts that are the most populated, but also information such as densely populated apartments or barren lands.
While spatial heat maps are useful when visualizing population density, they can also be used to visualize other types of density. An example is analyzing the density of website visitors’ attention in web design and marketing. A company looking to redesign their webpage can analyze user interactions of a specific type, such as where a user scrolls to, what they click on, or where they hover their mouse. This can then be used to determine which parts of the website visitors are paying the most attention to, if a new call to action (CTA) button is working, and more.
When should I use a heat map in qualitative data visualization?
Heat maps can be used all the time! As ambitious as that may sound, heat maps are a great way to intuitively visualize insights. They are best used when you need to show relationships between variables, and it is better to show in a visual way opposed to raw data. In addition to the examples listed above, heat maps can also be used for:
- A/B testing
- Content marketing
- UX/Usability testing
- Conversion funnels
- Website analytics
- Customer distribution
If you’re interested in learning more about heat maps and how HelloInfo can help you utilize them, Schedule a call with us.
Here at HelloInfo, we help our clients answer questions so they can make strategic decisions. Our HelloHow? blog series outlines different frameworks and approaches to carrying out strategic intelligence research. For other HelloHow? articles, see our blog, Spotlight.
