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Create a Bubble Map

Quickly identify areas for further investigation with Bubble Maps.

One of the primary reasons many Sales Managers use data visualization is to quickly identify patterns and trends in their sales data. When analyzing sales data on a map, there are several options available in eSpatial to do this. However, one the most common ways to quickly get an understanding of your location data is a Bubble Map Analysis which gives you a very quick look at your data in a summarized fashion.

Bubble maps are one of the best ways to communicate proportional location-based data in a clear and concise way. Like Heat Maps, Bubble Maps summarize your data by regions, different circle sizes represent different value ranges; the large the circle the higher the aggregate value for that region. For Example, to quickly identify and analyze the volume of sales, or customers in each state or sales territory, analyze performance over regions, and gap analysis.

Many Sales Managers use this type of analysis to quickly identify areas for further investigation, such as identifying regions with low customer concentrations and using this information to put more marketing spend into these regions, with the aim of increasing their customer base, and revenue.

Learn how to create a Bubble Map in 3 easy steps

1: Click the Analyze button and the Bubble Map option
Bubble Map Analysis
2: Select the Point and Regional Datasets to be used

Once Bubble Map is selected, you will need to then select the Points and Regional dataset to be used in the Bubble Map. For example, if your customer sales data is based in the United States and you want your data to be summarized by State, then select your customer dataset and select US States from the dataset library.

Select your points data for bubble map analysis

3: Click Complete to generate your Bubble Map

Click Complete and your Bubble Map will be generated with your data summarized by region. The image you will see first will also have all your points data displayed on the map. You can hide these points in the legend by clicking the eye icon beside the dataset.

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