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Trade Area Analysis Methods, Theories, & Techniques: Explained

June 6, 2021
by
Kate Blumberg

SafeGraph’s location data helps businesses perform trade area analysis, which can give them the information critical to making decisions on store location and layout, marketing strategy, and more.

But there is more than one way to analyze a trade area, and which one is right for your company will depend on what kind of business you run and what your priorities are. To demonstrate, we’ll walk you through the strengths, weaknesses, and theories behind three trade area analysis methods that you can perform with SafeGraph data:

We’ll start with the more basic trade area analysis techniques, and then get into the more advanced ones.

Top 3 trade area analysis methods

To show how deep (or shallow) you can go with trade area analysis, we’ll look at samples of three models of increasing complexity. We’ll start with one that relies solely on geographic distance, then look at one that takes ease of transportation into account. We’ll finish with a contemporary model that uses anonymized location-based data to map out where shoppers at a particular store are coming from.

Method 1: Buffer

An example of the buffer model of trade area analysis

The buffer technique is the simplest of the trade area analysis theories. Basically, it assumes all people within a certain geographic distance (or distances) from a store will potentially be that store’s customers. Businesses can then proceed to analyze the demographics of those who fall inside this catchment area (or areas).

Buffer analyses can also include a focus on competitor locations. For example, analysts may draw buffers around competitor locations to compare trade areas. A rule of thumb often used is that when the distance between two locations increases, the connections between them (in this case, similar trade areas) decreases. This is commonly referred to as the Huff Gravity Model and can be helpful for trade area analysis.

The buffer model is good for getting a general, non-technical idea of a store’s market share. However, a major weakness of this model is that it doesn’t account for transportation routes (roads, train tracks, ferry routes, etc.) or lack thereof. 

As a result, it may include people who would likely not visit the store because of difficulties in actually getting there. It may also exclude potential customers who would visit the store because the surrounding transportation infrastructure makes it easier to visit that store than an alternative.

Method 2: Walk or Drive Time

Walk/drive time theory measures a store’s market share while factoring in geospatial data such as transportation mode speeds, route shape/length, speed limits, and traffic volumes at different times of day. This data is used to create a trade catchment area for a store based on how efficient it is timewise to get to the store using surrounding transportation routes and options. In this way, the walk/drive time model accounts for terrain and other obstacles that the buffer model doesn’t. 

An example of trade area analysis by measuring walk or drive time

Walk/drive time theory measures a store’s market share while factoring in geospatial data such as transportation mode speeds, route shape/length, speed limits, and traffic volumes at different times of day. This data is used to create a trade catchment area for a store based on how efficient it is timewise to get to the store using surrounding transportation routes and options. In this way, the walk/drive time model accounts for terrain and other obstacles that the buffer model doesn’t. 

This model is good for convenience stores and other store chains that expect customers to want the closest or easiest option, and be in and out quickly. However, it still has two shortcomings. The first is that it relies on having up-to-date information about the status of transportation routes in the trade area. Walk or drive times can be affected by construction, car accidents, and other disruptions, so they’re sometimes only as accurate as the latest data.

The other issue with the walk/drive time technique is it assumes the most important factor when determining the likelihood of someone shopping at one store over another is which one is closer or easier to get to. However, there may be other considerations. For instance, a store that’s farther away may have lower prices, a larger area and/or bigger inventory, or specific items that a closer store doesn’t have.

Method 3: Mobility Data

Method 3: Mobility Data

The mobility data technique uses anonymized location information from smartphones and other GPS-enabled devices to determine where a store’s customers generally live, based on where they are at certain times of the day.

Mapping shoppers at a Costco store in Richmond, California using mobility data

The mobility data technique uses anonymized location information from smartphones and other GPS-enabled devices to determine where a store’s customers generally live, based on where they are at certain times of the day.

This theory is currently one of the most advanced techniques of trade area analysis, and has many advantages over the buffer and walk/drive time models in application. One is in figuring out what stores are or aren’t competing with yours, based on where your clientele is coming from.

For example, the map above uses shades of blue to represent the general areas in which visitors to a Costco store in Richmond, California (the single red dot) live. Using a buffer or walk/drive time model, one might assume the Target stores in Albany and Berkeley would be Costco’s main competitors. However, the mobility data shows that most of Costco’s shoppers come from the north and east. So the Target store in El Sobrante is actually a bigger competitor, despite being further away.

In this case, the demographics for shoppers at Costco can’t simply be explained by how easy the store is to get to or how far away competing stores are. There must be other factors at play, such as pricing, store size, or specific inventory. In this way, the mobility data model gets around a key weakness of the buffer and walk/drive time models. 

We hope this has given you a better understanding of some of the techniques and benefits of trade area analysis. For a more thorough discussion on why trade area analysis is important, check out our article on the 4 key benefits of trade area analysis in scouting a new store location.

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