3 Methods of Calculating Catchment Areas & Where to Get the Data

Trade area analysis is a complicated process that requires significant effort and consideration to get right. To ensure that you are relying on accurate data visualizations, you need to make sure that you are calculating your catchment areas correctly for your needs.

Catchment areas can be calculated by simple buffer zones, walking or driving time to the location, and even mobility pattern data, painting a vivid picture of where your customers visit your business from.

To help you calculate catchment area, we cover the following:

Let’s dive into the three methods for calculating catchment areas and help you decide which to use depending on the analysis you are trying to perform. You can also check out our ultimate guide to trade area analysis to learn more about trade areas and how to analyze them.

There isn’t a single way of calculating a catchment area, as there are a variety of values you can use to measure trade areas such as distance, travel time, and mobility patterns. Calculating the trade area is not about following a set formula, but deciding on the method you will use to define your catchment area.

Below, we cover the top three methods for calculating catchment area:

Method 1. Buffer trade areas

Buffer trade areas create a buffer area around the locations that are of interest to you. These are most commonly based on a distance from the POI, but they can be adjusted in a number of ways.

Creating a buffer trade area map showing your existing locations and all competitor locations within those regions can be a great tool. To do this, you’ll need to:

1. Create or obtain a file of your existing store locations for analysis
2. Create or obtain a file of existing competitor locations using SafeGraph Places
3. Create a buffer around the locations (whether yours, your competitors’, or both)
4. Join the two files or create a visualization to show your trade areas (keeping an eye out for potential cannibalization) and competitors with trade areas that intersect with yours.

This will give you a catchment map of your store locations, their buffer zones, all competitors in those buffer zones, and their trade areas. This makes it easier to visually compare your locations to competitors, gaining a picture of each individually, locations in a set region, or all of them as a whole.

Method 2. Walk and drive time trade areas

Walk and drive time trade areas map the distance from the POI based on the time it takes to walk or drive there. Essentially, this involves pinpointing the location you want to analyze and creating an isochrone map displaying areas surrounding the POI based on walking or driving time. The map can be set up to display specific intervals of time, depending on what is important.

For a Starbucks, walk and drive times of 3, 5, and 10 minutes may all be useful. However, for larger, less common stores like Ikea where visitors will require a vehicle to transport the items they purchase, drive times of 10, 30, and 60 minutes may be more useful.

1. Create or obtain a file of your existing store locations and any competitors you want to include for analysis 
2. Upload the data into a BI or GIS program that includes drive and walk time tools
3. Define your time parameters and run the tool
4. Join the two files or create a visualization to show how the trade areas relate to each other and may impact your business

You can use these to map trade areas for multiple locations, helping you see where there are gaps and overlaps in your trade area. As you can see from the example of the catchment areas above, mapping multiple locations shows you where the closest location is to your visitors, helping you identify where to expand or close down locations, how to avoid cannibalization, and what the competitive landscape looks like.

Method 3. Mobility trade areas

Mobility trade areas determine their catchment according to how consumers move. Rather than relying on a simple store radius based on distance, the catchment area will be defined based on mobility data showing store visits with origin census block groups (CBGs) and other brands visited that day/week. This not only creates a more dynamic area, but enables demographic analysis and brand affinity insights.

This allows you to create a variety of data visualizations of trade areas based on different variables related to customer mobility, such as demographics, other stores visited, dwell times, and more. Creating multiple (or interactive) catchment maps based on different mobility factors allows you to get a clear picture of your catchment area.

1. Create or obtain a file of your existing store locations and any competitors you want to include for analysis
2. Layer in mobility data
3. Join mobility data to your store location data to see how and where people move throughout the day
4. Add in any other enriching data, like demographics or consumer transaction data

This will give you a catchment area based on actual human movement instead of inferred location geographic relationships. There are multiple catchment maps that can be created this way, factoring in demographics such as age, income, and more.

It’s important to get store location data for yourself and any competitors or complementary businesses you want to analyze, as well as mobility data for those points and any enrichment information you can, such as demographics data.

SafeGraph’s point of interest (POI) data provides business listings with geographic coordinates and brand details that can form a solid base for catchment area analysis. Also provided by SafeGraph is a free, cleaned census demographic dataset to further enrich trade area analysis.