There are several strategies that companies can use to locate new stores.
The “piggy-back” approach is where a new store is located on the basis of another company’s location strategy. This approach works as long as the strategy of the copied retailer works.
An aggressive form of piggy-back is to place a new store in the middle of a mature market. This strategy is used by larger companies to diffuse risk. An example of this is Goo Goo’s carwash chain, which has placed express exterior outlets in mature and competitive markets in several metropolitan suburbs.
Another strategy to diffuse the risk is to open a hub in a major city and then rollout more stores into other nearby markets. This strategy was used by Mike’s Express Carwash to develop their chain of exterior-only outlets in Indiana and Ohio.
Diffuse the risk
The qualitative aspect of identifying a good location involves developing a gut-feeling based on experience and observation. The quantitative aspect involves the use of models that attempt to describe how many customers are going to come and how much they are going to buy. This includes analogue and gravity models, regression analysis, and retail market analysis. These models are based on assumptions about the attraction that moves people toward certain retail destinations.
None of these models are perfect. Without gasoline in the mix, gravity models rely on much less historical data which is typically biased to stores with above average performance.
Analogue and regression models are easier to understand but require a high degree of customization to reduce errors associated with non-linear relationships and outliers that can skew the results.
Market analysis models are less expensive to implement but the results must be combined with other techniques to properly allocate potential sales to the store level.
A working example
Let’s consider an investor who is building an express exterior in a mature market. In this case, the company decides the best set of circumstances exists near Carwash A.
Carwash A is successful. The selected location provides the most overlap to “lift” business from the other competitors in the area. The highway provides good traffic and business counts. The demographic profile is robust. There are no express exterior facilities in the community.
The company plugs the minutiae into a forecasting model and develops sales projections for the site located next to Carwash A. Are the projections reasonable? Did the model(s) do a good job of assessing the degree of entrenchment and customer loyalty of Carwash A?
Is the relative attractiveness of the new store enough to lift 40 or 50 percent of Carwash A customers? Are the assumptions about highway capture rate valid in a situation where 3 outlets must now share the same traffic flow?
These are tough questions for investors who are facing a breakeven point of 70,000 or 80,000 washes a year.
Models provide companies with a way to use mathematics and statistics to describe the real-world and hedge risk. However, their use must be combined with intuition and observation to provide the best ground truth about location and opportunity.
Developing a location strategy and building a store forecasting model involves time and expense. However, given the increasing cost to build a new wash and the competitiveness of many markets, this has become something that most investors cannot afford to avoid.
Robert Roman is a former carwash, express lube and detail shop operator and is president of RJR Enterprises (www.carwashplan.com
), a leading consultant to the carwash industry. Robert is a member of International Carwash Association and PC&D’s Honorary Advisory Board. He can be contacted at firstname.lastname@example.org