Aggregate by value tool

A robust feature that uniquely empowers you to merge and scrutinize spatial data based on specific attributes or criteria

Sign up for a free 14-day trial
Aggregate by value tool
What is aggregate by value tool
Video transcript for What is aggregate by value tool

The aggregate by value tool is a great way to summarize, analyze, and present your insights. And it does simplify your data analysis process.

So for example, in this case, I want to find out my sales by sector. So using the tool I'm just going to select from the dataset, the industry sector, and then the table below shows me the key metrics I need for further analysis.

Why use the aggregate by value tool?

Group your data

Group your data

The Aggregate by Value tool allows you to group data points on a map based on shared attributes. For instance, you can aggregate sales data from multiple locations by sales territory or product category.

A typical query might be to aggregate (or combine the product sales data of multiple areas) product sales within a sales region.

Summarization of map data


The tool summarizes the data for each group after aggregating, based on selected metrics like sum, average, median, or count. It is immensely helpful in making sense of diverse data sets, such as the total revenue from different regions or the average number of insurance claims in various cities.

Visualization of aggregated data


The data can be summarized and presented through visual maps like heat maps or cluster maps, which are available in eSpatial. The visualizations help you uncover new (and possibly hidden) insights in your raw data.

What are the use cases for aggregate by value?

  • Sales planning: Revenue operations might aggregate sales or product sales data by state, county, Zip, or territory and identify new growth opportunities
  • Market planning: Marketing operations might aggregate campaign or event data by state, county, Zip, or territory and identify new growth opportunities
  • Urban planning: Planners might aggregate population data by neighborhoods to determine where services or infrastructure improvements are needed
  • Retail analysis: Businesses can aggregate sales data by ZIP code or region to identify high-performing areas and adjust marketing strategies accordingly
  • Public health: Health officials could aggregate disease incidence rates by locality to identify outbreaks and allocate medical resources more effectively
  • Environmental studies: Researchers can aggregate pollution levels by geographic regions to identify areas of high contamination and correlate these with potential sources

You appear to be offline at the moment, this notice will disappear once your device can connect to the internet again