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How can a trade area be analysed?

Posted by Jacob Pescini on 23-Jun-2014 11:00:00

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Trade area analysis has its focus on locating and describing the target market. Analysing the trade area is important to determine the reach of existing and new store locations and if sufficient target customers reside within the trade area. To analyse trade areas, the use of Location Intelligence is essential to effectively model physical trade areas. The accuracy of these models will depend on the number of variables being considered, like customer location, competitors and consumer spend or attitudinal data. 

Drivetime_boundaries

So how can a trade area be analysed?

  •          Drive-time calculations
  •          Natural Boundary
  •          Closest center
  •          Gravity Models
Drive-time Boundaries

A very common form of trade area modelling is to create drive-time boundaries around existing or potential sites. The use of drive-time boundaries can range from the very simple e.g create a 20km drive-time using customer location and spend data is useful when there is a large network of sites across a geographically and demographically diverse area. When customer location data is unavailable then Census and segmentation data can be used as a substitute.boundaries around all of my stores, to more complex boundaries using existing customer or demographic data. By using customer location and spend data in combination with drive-time analysis, analysts are able to determine how much spend occurs within a given distance of a site. For example, one site may have 70% of total spend derived from customers less than 10km from the site while another site may have 70% of total spend derived from customers less than 30km from the site.

Using customer location and spend data is useful when there is a large network of sites across a geographically and demographically diverse area. When customer location data is unavailable then Census and segmentation data can be used as a substitute. 

Natural Boundaries

Where the site network is located across a wide geographical area then the use of natural boundaries can be used to define site trade areas. These natural boundaries are typically things like rivers and mountain ranges and they inhibit the accessibility to multiple locations and force people to favour one destination over another. They are typically defined with little emphasis on modelling and more on “gut feel”. The use of natural boundaries for trade areas is rather coarse and the limitations of such a model need to be clearly defined. 

Closest center

Closest center trade area modelling is similar to natural boundary modelling but the areas are built on the assumption that each site has the same attractiveness as any other and that a customer will always travel to the nearest site in the network. Trade areas built using this method have a similar coarseness to natural boundary trade areas and have to be used with caution and understanding of their limitations. They work best in urban areas where there few natural barriers to access.be used to define site trade areas. These natural boundaries are typically things like rivers and mountain ranges and they inhibit the accessibility to multiple locations and force people to favour one destination over another. They are typically defined with little emphasis on modelling and more on “gut feel”. The use of natural boundaries for trade areas is rather coarse and the limitations of such a model need to be clearly defined.

Gravity Modelling

Trade areas can also be generated using probabilistic gravity models that take competition and attractiveness into account to predict the likelihood a customer will visit a store. Numerous attractiveness variables can be added to create an appropriate model such as product range, site size, car parking and public transport access to name a few. Of course, these types of models are not restricted to zones or boundaries. iSite Media used a form of gravity model to calculate the probability to see for buses travelling along bus routes in New Zealand. The model enabled iSite to validate why certain bus routes were more valuable in advertising certain products than others based on the “trade area” of the bus route.   

In summary, there are a number of ways in which trade areas can be defined. The more data you have about the existing or potential customers for that site the more complexity you can add to your trade area modelling. Of course, how you define your trade areas is only one of a number of questions you need to answer when deciding on retail network changes. To ensure you know about using location intelligence to it's fullest potential to answer these questions download the white paper: New Location Perspective in Retail: In the Zone

White Paper: New Location Perspectives in Retail

Topics: Retail Location Analysis, Retail Network Planning, Location Intelligence, trade area profiling

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