Site Selection Best Practices Q&A: Why Precisely Defining Trade Areas Matter

Bob Buckner

Trade areas with customer dots in the Kansas City market

In the first article of a new Intalytics series exploring best practices in site selection research, industry experts Bob Buckner and Justin Tischler discuss the importance of accurately measuring trade area extents – and how understanding consumer trip patterns will help brands identify viable real estate opportunities.

So that we’re all on the same page for this discussion – can you describe for us what a “trade area” is?

Bob Buckner:  A trade area in its simplest definition is the geographic area from which the vast majority of revenue (or customers) originates.  It is not at all unusual for retailers, restaurants, and service and health care providers to serve multiple disparate trade areas depending on the trip origin or destination associated with each customer.  For example, most trade areas associated with retailers are residence-centric; that is, the majority of retail shopping trips originate from each customer’s place of residence. Conversely, restaurants almost always serve multiple trade areas which typically reflect not only customers residing in the vicinity of a restaurant, but also customers working or shopping near the restaurant.

What are some factors you take into account when defining trade areas?

BB:  It is important to not simply rely on generalizations to approximate a trade area.  We consider numerous factors such as drive-time, the presence or absence of other units in the same brand, and urbanicity.  Additionally, we also look at barriers that would naturally impede access to a location – natural barriers like rivers or lakes, or non-natural barriers like a major highway.  Ultimately, the significance of these factors is implicit in the actual sales or customer distributions associated with each location, as the map below illustrates.  Based on a rigorous analysis of individual existing locations, Intalytics is able to quantify the extent to which each of these factors “matter”.

An example trade area is visualized against a customer distribution below.

Trade area visualization with customer dots

Justin Tischler:  Regarding methodology, I like to think of it as a “good, better, best situation” when it comes to trade area definition approaches:

Good – concentric mile ring(s) around the location

Better – concentric drive-time ring(s) around the location

Best – uniquely modeled and defined trade areas for an individual location

If you have a location that is situated in a suburban area on the periphery of a major metro area, we’ll very often see the sales density (and trade area) for that location extend 20-30 minutes into the country, but only 10 minutes back into the city. That’s difficult to account for with concentric ring methodologies, and a big part of why we follow the data and take the more rigorous approach we do.

Once the trade areas are built – so what? How are these put into practice? What can you learn from them?

JT:  It is really critical to understand that not all consumers patronize a brand in the same way.  Consumers who reside or work locally are those that have a convenient opportunity to utilize a brand’s services.  Their convenience-driven visits are foundational to customer profiling, predicting future sales, and estimating cannibalization, and it is these consumers upon which trade area extents should be based.  Consumers coming from some larger distance – travelers from out of town, visitors to a nearby attraction – defy those patterns of convenience.  So the trade area can be used as a “line of demarcation” to isolate individuals that patronize a location based on convenience versus those that had something else draw them to the area.  Another practical benefit of accurately-defined trade areas for existing units is that it provides an easy-to-use visual tool that market planners can use to identify infill opportunities and to visually approximate the impact from new unit openings.

BB:  Understanding the trade area extents of existing units and how they vary by market size, urbanicity, location type (mall/off-mall), prototype, etc. provides a means by which one can estimate the trade area extent(s) of future locations.  Having defined trade areas for an existing database of units, one of the first models Intalytics develops is a model that accurately predicts these known trade areas extents.  Knowing that we can accurately model the extents of existing trade areas provides us confidence that we can accurately predict what the trade areas for future units will be.  It is these trade area definition models that are leveraged as a first step in generating a forecast for any future location.

Why does accurately defining trade areas for prospective locations matter so much?

BB:  For me, this is where the rubber meets the road.  Very simply, if trade areas for future locations are over defined – regardless of the rigor used to develop a forecasting model – you’ll over-forecast that location’s potential.  Conversely, you’ll under-forecast if the trade area is under defined.

JT:  Bob’s comments underscore “why methodology matters”.  Our approach considers both the characteristics of the location and the characteristics of surrounding neighborhoods when estimating trade area extent, because we find this gives the most accurate results.

However, flexibility is important here – there are always going to be unique situations when applying a model, and being able to adjust on-the-fly for location market conditions is part of how we’ve built our forecasting platform.  And with mobility data, it’s possible to study the sales distributions and trade areas for competitors or shopping centers near a unit under consideration to serve as a point of validation against the trade area you define.

Interesting in learning more about Intalytics’ approach to studying customers and trade areas? Reach out to our team today to start the conversation.

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