Why a Retailer Needs to Know Its Trade Area and How to Begin Measuring It

Defining Trade Area

A store’s trade area, also called its catchment, can be likened to its sphere of influence. It measures how far its customer base extends. But there is always the likelihood that a passing Norweigan tourist visits a store in Pune, or even the next visiting US president. In fact, if all infinitesimal probabilities be included in defining the trade area, it would include the entire globe, and even the universe if the one in a trillion trillion probability of a spaceship landing in front of that Pune store be also considered. Hence, a trade area definition is restricted to a bulk fraction of the (literally) universe of customers that a store attracts. Typically, this varies from 60-80%.

Why a retailer needs to know its trade area is asking why a politician needs to know the constituents of the district he contests elections from. Just like a politician cannot change the demographics of  his constituents, a store cannot change the demographic facts of its site. It might choose to ignore it only in a totalitarian state where supplies and competition are both artificially kept scarce. It might shape the habits of its customer base, slowly and incrementally, but that’s another story, and merely nuanced adjustments to a set reality shaped by metanarratives of geography, history and sociology.

To be successful, a retailer has to become the store that its community needs and a successful trade area analysis defines exactly what this community is and what it needs, explicitly and implicitly.

Benefits of Trade Area Analysis

To list some of the obvious benefits of trade area analysis are:

1. Selecting the right site to fit the retailer’s proposition
2. Defining sales and market share targets
3. Competitor threat analysis
4. Minimizing cannibalization
5. Finetuning proposition to map the site to the correct store cluster
6. Defining the geographic range to direct maketing towards
7. Preempting shifting trends because of shifts in trade area variable

Estimating Trade Area

The easiest way to start estimating the trade area is to build concentric circles around the site based on distance from the site. The image in Figure 1 shown is from a Californian city. (Website reference below)

The rings here are thrown at a distance of 3, 5 and 10 miles. The retailer might assume from historical evidence that 60% of its customers come within the first ring, another 25% between the first and second, and 10% between the second and third ring. That adds up to 95%. The rest of the 5% the retailer might leave to those instances of somebody from the other end of town passing by, or those Norweigan tourists and spaceships that he can really do nothing about.

The size of these rings is determined by the format and size of the store, population density of its catchment, the competitive intensity, and how well its proposition fits the needs of the customer base. The major determining fact is the format – bigger formats have larger trade areas. A hypermarket is less likely to feel the heat of a neighborhood market three miles away, but the neighbourhood market will definitely feel the breath of the hypermarket down its collar. Size does matter.

The other major factor, as important as the format size, that determines the size of the rings is the population density.  In a sparsely populated area, ring sizes are going to be larger. However, the ultimate size of the rings is going to be determined by competitive intensity. However, sparsely populated areas usually tend to have widely distributed competitors since each retailer needs a critical mass of customers to be profitable and, unless the retailer has an absolutely winning proposition, opening like stores near a credible competitor in a sparsely populated geography is moving towards a mutually assured destruction.

Another method to draw trade areas is to use driving times, since constant radii that build the concentric circles do not account for road networks, traffic conditions, physical barriers. It has been empirically observed again and again in retail that customers choose stores on the basis of driving time proximity before distance. On Figure 1, the driving time is shown by the pale blue line.

The limitation of drive time technique is that it relies on accurate road and traffic conditions, which might vary more frequently than demographic variables. Also, it does not consider the target customer for the retailer. Assuming the pale blue line in Figure 1 denotes a 15 minutes drive-time and 60% of store sales, this might be valid for if a store attracts all types of customers in its catchment. But if a specific store, say a home-furnishings specialty store catering to young couples, a more valid catchment might be the upcoming block on the east of this site where the young couples are buying their first homes. Hence, many retailers use a gravity model to estimate their trade areas. This measures the strength of the gravitation pull of the store over the relevant customer base versus the competitors and uses various distance-decay algorithms to estimate the trade area in, again, concentric rings of probability. Again, they suffer from the same shortcoming as the distance-based method of not taking in actual road and traffic conditions, and physical barriers.

Ultimately, the method to estimate its trade area that an analytic retailer chooses depends on the data it has and its time-tested practices. This is but the beginning. In the next article, we would look at the major trade area attributes that retailers use to select a site and define its sales and share of wallet targets.

Website link: https://www.cityofrsm.org/depts/development/economic/local_business_information/trade_area.asp

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