There are many different aspects to the current practice of market assessment, and different interests will look at the question from different perspectives and use analytic tools to answer the questions they are concerned with.  This is made possible by the increasing availability of data.  Demographic maps, projections, consumer surveys etc. and GIS analysis tools allow inquisitive people to pose questions and understand the local supply, demand, competition and access for different types of markets. The overview a developer will examine is the “Area Demand” which quantifies demand through employment, population estimates, demographic in, which formation, income and retail sales.  Retailers increasingly use “Consumer Demand” analysis that qualifies the type of demand through market segmentation,  “psychographic” profiles, and local consumer buying preferences.  “Market Share” analysis evaluates the existing competition, and “Trade Area Analysis” helps in location selection to optimize market share.  In short, such analysis determines what to build and where to build it.

 

The theories developed in the 1930s of central place / agglomeration and gravitation are still the basis of thought for retail theory.  (However, I think it is interesting to understand the context that these theories were developed in, and their intended application and implications, but we will get to that later.)  The big ideas can be summarized as follows:

People will travel the shortest distance possible to, for example, buy a cup of coffee. At the same time, larger concentrations of services that provide choice and utility will attract customers from larger distances. You might go a little bit further to get a cup of specialty coffee at a place that also sold your favorite newspaper.  Understanding the balance of distance and utility of a trip, the retailer can estimate the likelihood of how many people will be drawn the extra distance to buy both a specialty coffee and a newspaper rather than suffer the instant brew available more conveniently.  This is the generalized logic of increasing grocery store sizes to capture shoppers from a larger trade radius, and is the basis of “Gravity Models” to predict the ability of larger stores to “out-draw” the competition.

 

 

 

 

In 1931 William Reilly at the University of Texas in Austin hypothesized a law of retail gravitation (that was restated by Curtis Publishing Corporation in 1947 as follows):

M=D/1+sqrt(P1/P2)

This equation determines (estimates, really, but more on that in a second) the point of indifference between a customer going to one location versus another based on the population of each center and the distance between them and the customer.  This law establishes a relationship between the utility of size versus distance to a location.  A later version of this theory in 1963 by David Huff framed the relationship in terms of probability, laying the ground for estimating market capture.  The framework of all of this analysis underscores the importance of the two previously mentioned factors: utility (of agglomeration, and with it choice of products), and time.  

 

Although it is commonly referred to as a law, Reilly’s hypothesis has been verified with only moderate degrees of accuracy, suggesting the principle is sound, but the exact relationship varies by location, and may have other factors (perhaps qualitative elements) that are not accounted for.  Also, Reilly determined the “size” not by the square feet of retail space, or the variety and aggregation of services offered, but by the local population, that was used as a proxy presumably since at the time in 1931 retail was still concentrated in population centers.

 

Reilly’s Law of Retail Gravitation attempts to quantify the relative value of agglomeration.  This articulates the utility of a site that offers greater benefits for the customer for the distance traveled.  When a customer can satisfy many needs with one trip, even if the trip is longer, they will make the trip because the “utility” of the experience is perceived to be higher.  This is the strategy pursued by a regional mall that includes a wide variety of shops as well as food and entertainment in order to increase the perceived benefit to the consumer for the sunk cost of the trip.  Another example of this utility is when the quality, type of goods, or pricing is simply unavailable elsewhere, thus making the perceived value of the goods or experience more important than the cost of getting there.  An example of this is a high-quality restaurant that may be located in an out-of-the-way place but still attracts customers from miles away.   Similarly, Walmart made it’s way establishing stores in rural places where people were under-retailed and were accustomed to driving many miles to shop.  By providing a wide selection at discounted prices, (promoting a perception of utility) it was able to draw rural customers from large distances.  

 

 

One interpretation of retail gravitation is that it encourages retailers to build the largest facilities possible to “out draw” competition.  Where densities are lower, larger boxes are required to draw a sufficient market from a larger area.  (Look at the Walmart model to better understand how a big, juicy retail magnate on a rural highway can draw from many distant rural communities with low enough densities that do not support competing local services.)  This logic, as a response to servicing low density areas, has caused new suburban retail to rely on size as its primary competitiveness and creates a culture of “category killers” where retailers either dominate a market or go out of business.  

 

At the same time, there is a hierarchy of types of retail, based on the frequency of customer use, and the time cost of the trip.  Some very basic questions differentiate types of retail markets: how many people need what is being sold, how often do they need it, and how far do they have to go to get it?  People need groceries often, while appliances are needed only once in a very long time (depending on how reliable the machine is, of course).  Stores with goods that require lots of visits annually are called “high-frequency” uses; others, such as appliance stores have fewer visits and are considered “low-frequency” uses.  As the frequency goes down, typically, there are fewer shops.  Consequently there are more grocery stores than appliance stores for a given market, and people are willing to travel farther to go places with greater choice for appliances.  It should not be surprising then, that “category killers” tend to best work with low frequency uses, where customers are willing to infrequently travel farther for better selection and price, allowing very large stores to service very large geographic areas.  

 

This frequency hierarchy is another aspect of value versus time as described by Reilly and Huff.  The shop with the highest perceived utility for the amount of time spent getting it will out-compete other locations.   We have seen above how this has played out with category killers in low frequency uses.  For very high frequency shopping trips, however, this means the closest or the most convenient shop to the consumer is likely to gain the sales—this is the retail strategy of convenience markets, where price of goods is a secondary consideration.  This also means that urban shops, with easy access to the city residents, are still positioned to be the closest and most convenient retail services.  

 

These theories elaborate the governing laws that show how retail locates as close to it’s market as possible and in agglomeration of sufficient size to provide the perception of utility to the customer.  They also help explain why the demographic shift in population to lower density regions and the highway and super-highway infrastructure shape the modern retail landscape.

 

-gk