B. Describing the Market

Effective retail location choices are made with accurate and detailed information. Decision makers need to determine which regions are "ripe" for development, and then need to go into those regions to find the right towns, and even the right parts of those towns. For example, Lowe's, the second-largest home improvement chain in the US, is based in North Carolina, but has been expanding rapidly in Texas. The Texas region was chosen for its rapid population growth, as well as sound economy. But it was important for Lowe's to select the right towns (which included Amarillo, Lubbock, Abilene, and the DFW area), as well as the right parts of these towns. For this reason, their Amarillo store is located on the southwest side, near many homeowners who are most likely to be doing home improvement projects.

Many retail decision makers examine geodemographic data about an area before committing to expand. These are often done by ZIP Code areas, or census tracts. Analysts look at population characteristics in these regions, as well as income, education, age, and many more descriptive variables. These are important because a retailer may choose what appears to be a good location, but it may not be good for that particular type of business.

Another factor of importance is the available media in a certain area. The ADI (Area of Dominant Influence) is a geographical area that has common media usage patterns (e.g., Amarillo's ADI extends into southeastern Colorado and southwestern Kansas). Some chains seek to conentrate development into particular ADIs so they can coordinate advertising (as well as minimize expenses).

Another aspect to consider is the size and shape of the trade area. Trade areas can be broken down into three concentric circles (or similar shapes): primary (with about 65-70% of the market), secondary (with 10-20%), and tertiary/fringe (the remainder). Included in the fringe areas would also be "transient" customers, those passing through a town on their way somewhere else.

The size of a trade area will differ by store and product type. For example, supermarkets have a much smaller trade area than a shopping mall. Wal-Mart considers the trade area for one of their supercenters to be as large as 90 miles any direction from the store.

Amarillo's trade area is shaped like an egg, with the heavier bottom part stretching to the south, and the tapered top stretching to the north. Amarillo is not at the center of this region, though; rather, it sits very close to the bottom. Whereas there are no other major markets to the north, west, or east for at least 250 miles, Lubbock beckons people to the south of Amarillo. Thus, the trade area extends into southeastern Colorado and southwestern Kansas, and includes some of eastern New Mexico and western Oklahoma, but extends only a little over 60 miles to the south (to about Kress).

Other factors to consider include the following:

• local competition
• local cystoms, preferences, etc.
• consumer behavior issues at the local level
• local economy
• local lifestyles
• accessibility
• availability of good retail locations
• visibility
• traffic considerations
• parking

Numerous statistics exist which are useful in sizing up a market. Among them are:

1. The Buying Power Index, which calculates the market's capability to buy. It is useful for forecasting the sales of commonly used products, but not narrowly-targeted products. Those product makers must fine-tune the BPI to include the necessary demographic variables of its target audience.
2. The Sales Activity Index, which compares a city's percentage of total US retail to sales to its percentage of total US population. A ratio greater than one indicates a city that is more than carrying its weight, whereas a ratio of less than one signifies a weak market.
3. The Quality Index, which divides the city's BPI by its percentage of total US population. This index value (100 is the baseline) indicaates whether a city has average or above/below average buying power.
4. The Retail Saturation Index, which is a measure of an area's capacity to consume its capacity to retail. It tells whether a market is under- or over-stored. Interestingly, some chains stores will enter an over-stored market because they are confident they can wipe up existing competitors.
5. Huff's Model, which relies on two variables (store size and distance from the store) to predict shopping behavior. Once the Marketer knows the consumer sensitivity to these two variables (i.e., the importance of them), he can calculates the probabilities of shopping at any number of stores in the trade area.

There are problems with the last model, because it only includes a limited number of inputs. For example, Huff relies on distance and store size (bigger is better). There could be, of course, numerous other mitigating variables that influence store choice.