Heat map

Quick definition: heat maps are a type of data visualisation tool that use colour to convey data points in a simpler format. The shade of colour in a heat map typically indicates the volume of a data point. For example, a temperature map of a country might use dark blue to show the coldest areas, a lighter blue to show slightly warmer areas and then variations of red to indicate the hottest areas of the country.

Key takeaways:

• The value of heat maps comes from their use of colour, which allows the person visualising the data to quickly understand the information being presented and its impact.
• Heat maps work especially well with data that includes a range of numbers, as different shades of a colour can be used to indicate more or less volume.
• Because heat maps rely heavily on colour, companies need to be aware of accessibility concerns when choosing which colours to use. If the target audience isn’t able to properly read the map, the map hasn’t fulfilled its purpose.

The following information was provided during an interview with Jen Lasser, principal product manager for Adobe Analytics.

What is a heat map?

What is the benefit of using a heat map over another type of visualisation?

What problems do companies run into when creating or using heat maps?

How do heat maps tie into a larger business strategy?

What data is best represented by a heat map?

Is there a set of features that all heat maps have in common?

What tools do you need to create a heat map?

What skills are required for heat map creation?

How will heat maps be used in the future?

What is a heat map?

A heat map is a two-dimensional visualisation revealing a relative intensity or volume, of data. It uses colour rather than digits, lines, graphs or other representations to communicate relationships between data values for sets that would otherwise be harder to understand. Think of an U.S. electoral map, for example.

What is the benefit of using a heat map over another type of visualisation?

The main benefit of using a heat map is that it brings colour into the mix to better convey data to the person that's reading it. It helps to appeal to more users, including both creative and logical thinkers, because it’s both easy to understand and interesting to view. But in general, using a heat map just allows you to have the data resonate with more people by presenting it in a visual way.

One of the most common heat map examples is a stoplight. When you see the green, yellow and red lights, you know exactly what you need to do, which perfectly explains the value of a heat map. By observing the colour of the light, you are immediately able to understand what action you need to take. A graphical heat map works the same way and offers the same value. A heat map helps to distil down the “so what?” of data by visually showing the insights that a user needs to take away.

What problems do companies run into when creating or using heat maps

Since heat maps rely heavily on colour, it's important that they're built with accessibility in mind. The colour scheme used in the heat map should, whenever possible, meet colour contrast and density standards, so that all users or recipients of that heat map can benefit from the indicator of colour.

You want to make sure that you're accounting for varying levels of colorblindness and choosing the colour scheme that will be able to reach the most people. If inaccessible colours are used, then you lose the layer of colour as a means of conveying your point and it becomes a hard visualisation to interpret.

How do heat maps tie into a larger business strategy?

For organisations that are founded around data and making data-driven decisions, being able to understand the data and pull out relevant insights is essential.

More companies are seeing the value of validating decisions with data instead of making decisions based on intuition. And it's important to democratise data throughout the organisation so everyone can make those informed decisions. When you're democratising that data or sharing it out, it's best to think about your audience, who's going to receive it and how they prefer to interpret data and take it in.

By using a heat map, along with other types of data visualisation, a company has a better chance of making sure all decision-makers are working from the same source of information and the same level of understanding.

What data is best represented by a heat map?

The best data to use with a heat map is any dataset that ranges in value or volume.

Heat maps can take many forms, but a common version is a geographic map overlaid with data. For example, a broadcast news programme might show a map of the population of the United States using a colour gradient related to the volume of the population.

Or if you're working in the financial market looking at any sort of stock data, using green and red to understand the market trends is a common application.

And in sports, for instance, if you look at a shot chart to see where players are shooting from on the court, that's often conveyed in a heat map. Heat maps can take a lot of different forms and represent all different kinds of data across different industries.

Relating specifically to digital analytics and digital experience data, heat maps are useful for analysing the effectiveness of a webpage and understanding user behaviour.

Heat maps can be overlaid on the webpage and combined with eye-tracking technology to show where people are engaging or looking most on the page. That's a common form of heat map that we see in our industry.

Is there a set of features that all heat maps have in common?

Because there are so many ways a heat map can be used, the only thing a heat map needs to gain definition is a colour range. Most heat maps also have legends so the viewer can interpret the information correctly.

What tools do you need to create a heat map?

Heat mapping tools can vary, but every visualisation fundamentally starts from data. Typically, you'll have a table of data. Going back to the map example, the table could be different locations and then the metric would be population size. And instead of just sending that table off to somebody and saying, "Good luck interpreting this," a heat map could then be overlaid on it, like an actual map of the United States or the world, with the colours applied to represent the data.

What skills are required for heat map creation?

Since all heat maps start from data, some level of data aptitude is necessary to produce a heat map. You can use Microsoft Excel, Adobe Analytics, business intelligence (BI) tools or any data aggregation solution as your starting point.

Next, you will use an analytics tool to review the data. Then, the visualisation aspect of it can either come from that same tool or you could design something yourself. You could even do it in PowerPoint if you wanted, just by layering together different shapes to convey colour and data points.

The best maps require very little explanation. If the person putting the heat map together has chosen the right application of colour and included a legend, a user should be able to draw the relationship that they need to draw and then quickly start to get value out of the heat map beyond that.

How will heat maps be used in the future?

Heat maps will continue to be important and used for even more applications, both in the context of business data and in the world at large. The impact of artificial intelligence (AI) and machine learning on data analysis, collection and transformation will also affect heat maps, as organisations will get more precise and relevant insights.

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