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.
In all of these options, the more data you have available, the better your analysis will be. To add as much information as possible about human movement and other businesses in your store’s catchment areas, use SafeGraph’s point of interest and foot traffic data.
Below, we cover the top three methods for calculating catchment area:
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:
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.
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.
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.
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.
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. SafeGraph Patterns data gives you access to mobility data at the POI and CBG levels, providing deep insights into movement patterns for various POIs and neighborhoods. Also provided by SafeGraph is a free, cleaned census demographic dataset to further enrich trade area analysis.
Pair this with data from the SafeGraph Shop and any internal data your company may have (such as customer addresses from a loyalty program, etc.) to further enrich your data and gain deeper insights.