What is a heat map?
A heat map is a geographical representation of data that highlights the density of data in gradients of color. Heat maps are one of the best ways to get a quick understanding of your data by summarizing it in a single view. Usually, higher density areas are indicated by warmer colors, such as red, and lower density areas are indicated by cooler colors, such as blue. There are two types of geographical heat maps: hot spot heat maps and regional heat maps. Hot spot heat maps are generally used to identify regions for deeper exploration or analysis. Regional heat maps are usually used for performance comparison, especially in sales and service organizations. For professional results, heat maps are created using a heat map generator.
Heat map generator
Heat map generators are mapping software tools that take your geographic data and organize it by its activity levels. In one click, this turns a table of data into a map where you can visually understand how your data is geographically spread out. You can easily see where density and performance exist, and how it varies across ZIPs or postcodes.
Two types of geographic heat map and where to use them
As discussed above, there are two types of heat maps we can generate.
Hot spot heat map
The first type of map is a hot spot heat map. Hot spot heat maps are used when boundaries aren’t important, but we want to understand patterns of high and low activity, and where they are located.
One common example of a hot spot heat map would be a customer location map. High levels of customer density are expressed by a dark shade, whereas low levels are expressed by lighter shades. You can modify the colors and shades to best present the story you are telling. You can see this shown at a US national level in the image to the right.
Regional heat map
A regional heat map (also known as a choropleth map) is one that uses graded differences in shading or color in order to understand the average values of some number in particular areas. For instance, the aggregate value or volume of sales for each state or sales territory is color coded into several ranges, with each color representing a value range.
Regional heat maps are used to compare numbers within the given boundaries. This allows you to:
- Get an overview of your market performance.
- Quickly identify high and low performing areas.
- Uncover trends in sales of specific products in particular locations.
- Quickly spot areas for further investigation based on the density of sales.
Which type of heat map should you generate?
Hot spot heat maps provide a much more detailed analysis of density trends, while regional heat maps are easier to compare.Which type of heat map you should use depends mainly on why you wish to compare the data. What decision are you hoping to make based on this data? If you want to compare different areas, for example, comparing data by ZIP code (learn about heat maps by ZIP code) or by state, a regional heat map likely works best. If you want to understand the local density, then a hot spot heat map will likely be better. The good news is that both look great and are easy to understand when presented to the rest of your team.
ZIP and post code heat maps
So for US data, that boundary will likely be one of the following:
*Note that running national heat maps at ZIP level may be limited for performance dependent on the data volume involved.
Similar datasets exist for other nations. Just check our extensive data library or get in touch with us through web chat (bottom right corner) to see whether your boundary data is included.
Why do businesses generate heat maps?
As mentioned above, the right map should help you make better decisions. So what business decisions are heat maps used for? Here are a couple quick examples.
1.Identifying clusters of your customers & getting an overview of your marketplace
This is a great application for sales and marketing departments. In the map below, you can see a sales organization in Kansas has used our heat map generator to map their potential customers (state population) against their office locations.
2.Refining distribution networks
Another example of using heat maps to identify customer density is when planning and analyzing your distribution or service network. You can use customer density heat maps to identify where to best locate each center. Then you can quickly see if a distribution center is too far away from existing customers or would provide a more efficient service if it was located closer to clusters of customers.
3.Analyzing third-party data to identify ZIP codes for marketing campaigns
Many marketing teams use heat maps to analyze third-party data. This analysis helps them decide where to run effective marketing campaigns. For example, a fashion retail store in Texas is planning to run a billboard campaign. Using a regional heat map of demographic data, they can quickly see which Texas ZIP codes contain the majority of their target audience.
This allowed the marketing team to make effective use of their budget and resources by planning and executing their campaign in these areas.
4.Identify areas for franchise expansion
Another interesting use of heat maps is for franchises looking to identify areas to expand. In this situation, the organization has mapped its existing locations (shown as stars) in comparison with customer inquiries (represented by the heat markers).
This gives them data they need to make informed decisions on where to locate their next franchisee.
5.Quickly spot customer trends or areas for further investigation
We mentioned earlier how regional heat maps are useful for comparing areas.
The example below shows a regional heat map of customer satisfaction rates nationwide (red being a low customer rating, while green is a high customer rating). This map quickly highlights which territories have a low customer satisfaction rating, allowing management to act quickly.
6.Where are our profits being generated?
It’s crucial for any company to understand where they are generating their profits. Heat maps are a wonderful way to demonstrate where your profitable customers are based, and how these locations compare with each other.
7.Where do we need more sales coverage?
Similarly, you could ask, “Where are our customers coming from?” These two questions are the opposite sides of the same coin. Understanding where your customer inquiries are coming from and matching that to your current sales coverage is a very common heat mapping use for sales.
As you can see, this helps to easily visualize what our addressable market currently looks like, and as a result we can quickly decide where our current sales coverage levels are appropriate or not. From here, it’s easy to reach decisions about coverage gaps and overlap.
8.Where do I start field selling?
A common challenge for any field salesperson is choosing the best place to begin. Heat maps can help the salesperson find pockets of opportunity and use them as a starting point.
9.How can I tell how my sales teams are performing, and where they need to develop?
Our final common use for heat maps is to compare. Even though there is typically only one number that matters, comparing salespeople based purely on one metric won’t give a complete picture. Heat mapping allows you to compare your salespeople with an understanding of the market realities they face.
Regional heat map generator
Creating a regional heat map is easy, just create a free trial account and then follow these steps:
1.Upload your point data
The first thing you need to do is add data to your map. This is the data that will form the basis for your analysis and will display as points on your map. This could be sales data, service data, demographics and more, with one row for each unique address.
Click the Add Data option from the control panel. Then click Upload new data and follow the instructions.
2.Choose your regional boundary (typically states, or ZIP codes)
Secondly, you’ll need to choose boundaries for your heat map. This is what defines which groups your data points will be included in. This is often done by state or three-digit ZIP code. You can select various types of boundary data from our extensive dataset library.
To add your boundary, simply select the Add Data and then Add from Library. Select the eSpatial datastore tab and choose your boundary. In this example, we’ve chosen US states. For more boundary options, visit our dataset library.
3.Start your regional analysis
From the Control Panel on the left side of your screen, select Analyze from below your dataset. From the options, select Regional Heat Map.
4.Combine your points and boundary datasets
Next, select the points and boundary datasets. In this case, the points data is Client Accounts, and the region data is US states. Then simply select complete to generate your regional heat map.
View your generated regional heat map
Below is the regional heat map you created with our heat map generator. It shows the states with the most client accounts. You can see what each color represents in the legend on the right side of the workspace. The default color range is from yellow to red. However, this can be changed in the styling options.
Need some help? Press the chat button in the bottom right of the product for assistance from a mapping expert.
Prefer to watch a video? Check it out below.
Hot spot heat map generator
1.Upload your point value data
The first thing you need to do is to add data to your map. This data should contain one unique address per row, as well as any value fields you want to add to the map. In your new Workspace, select the Add Data option from the control panel. Then click Upload new data and follow the instructions.
2.Select Style from the Control Panel
From the Control Panel on the left side of your screen, select Style from below your dataset.
3.Choose the heat map styling options
Next, you will need to select Heat Map from the Style & Color panel. From here, you will see various options allowing you to change and edit your heat map, such as the colors and radius of the hot spots and the data to be used in the heat map.
4.Additional heat mapping options
If you wish to see the originally mapped data expressed as pins on top of your heat map, tick Overlay Pins from the bottom of the menu. Color Snapping removes the noise around the edge of your heat map.
Exit the Style Panel to view the map you have created using our heat map generator. The legend in the top right of the screen will highlight the color range from low to high data density.
Configuring your heat map to be easily understood
The main use of heat maps is to help your users understand the story your data is telling. Using good design practices when creating your map is key to accomplishing this. When creating a heat map to represent your data, here a few design tips to consider:
1.Choose the right basemap
Because you’re using a varied palette of colors to represent different density bands in your data, the map you overlay this onto shouldn’t fight to compete with your data’s color palette or make it hard to interpret. Users looking at your map may be looking at it on a small monitor or they may be looking at the map from a distance, by muting the basemap’s colors the data will stand out more and be easier to understand at a glance.
2.Choose easy to understand colors
Choosing the right colors can help your users understand your data. We recommend using darker shades to represent high density and brighter colors in the same family to represent low density. This makes it easy to understand the data at a glance, like the population density map on the right.
3.Choose the right data display settings
How you cluster your data will determine if your users understand the story. If you’re creating a national-level map, then state-by-state data clusters are fine. But if you believe your users will want to drill down into an individual state or ZIP code, then having the data divided into sub-level clusters will give your users a more granular view of the data.
Heat map or color-coded map?
It’s possible to create a color-coded map using the eSpatial heat map tool manually, assigning specific colors to each region that appears on the map. However, an easier method is to link data to boundaries. You can do this when uploading data to eSpatial using the built-in wizard.
What’s the difference?
What’s the difference between these map types, you may wonder? A heat map is used for showing levels of similar data occurrence, while a color-coded map simply defines different variables in multiple regions (levels of occurrence are not expressed).
A regional heat map, which is a form of choropleth map, is one that uses graded differences in shading or color in order to indicate the aggregate or average values of some property or quantity in particular areas. For instance, the aggregate value or volume of sales for each state or sales territory is color coded into a number of ranges, with each color representing a value range.
Layer additional data onto heat maps
A heat map is often used as a basemap on which you can plot other data. Our heat map generator will create either, but the process for creation is different, as outlined above.
Imagine you run a chain of care homes across the US. A practical map you could create using eSpatial would show percentage levels of retirees per state. You can then plot your own business data on the map. For example, you can map the number of care homes you operate per state. This will allow you to spot opportunities for expansion in an instant.