Heat map

Heat map

Quick definition

Heat maps are a type of data visualization tool that use color to convey data points in a simpler format. The shade of color 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 color, which allows the person visualizing 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 color can be used to indicate more or less volume.

Because heat maps rely heavily on color, companies need to be aware of accessibility concerns when choosing which colors to use. If the target audience isn’t able to properly read the map, the map hasn’t fulfilled its purpose.

Jen Lasser is the principal product manager for Adobe Analytics. In this role, she meets with customers to understand their business needs and uses these interactions to inform the analytics product roadmap. Previously, she was a principal consultant in the Adobe consulting team, and prior to joining Adobe, Jen worked on both client and agency sides in marketing analytics.

How do heat maps tie into a larger business strategy?

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

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?

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

How will heat maps be used in the future?

Q: How do heat maps tie into a larger business strategy?

A: For organizations 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 off of intuition. And it's important to democratize data throughout the organization so everyone can make those informed decisions. When you're democratizing 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 visualization, 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.

Q: What is the benefit of using a heat map over another type of visualization?

A: The main benefit of using a heat map is that it brings color 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 color 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 distill down the “so what?” of data by visually showing the insights that a user needs to take away.

Q: What data is best represented by a heat map?

A: The best data to use with a heat map is any data set that ranges in value or volume. Heat maps can take many forms, but a common version is a geographic map overlaid with data. A broadcast news program might show a map of the population of the United States using a color gradient related to the volume of the population. 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. In sports, 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 analyzing the effectiveness of a webpage and understanding user behavior. 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.

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

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

Q: What tools do you need to create a heat map?

A: Heat mapping tools can vary, but every visualization 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 colors applied to represent the data.

Q: What skills are required for heat map creation?

A: 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 visualization 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 color and data points.

When it comes to reading a heat map, the best maps require very little explanation. If the person putting the heat map together has chosen the right application of color 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..

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

A: Since heat maps rely heavily on color, it's important that they're built with accessibility in mind. The color scheme used in the heat map should, whenever possible, meet color contrast and density standards, so that all users or recipients of that heat map can benefit from the indicator of color. You want to make sure that you're accounting for varying levels of colorblindness and choosing the color scheme that will be able to reach the most people. If inaccessible colors are used, then you lose the layer of color as a means of conveying your point, and it becomes a hard visualization to interpret.

Q: How will heat maps be used in the future?

A: 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 organizations will get more precise and relevant insights.

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