By Guy P. Abramo

Convenience and petroleum retailers constantly seek opportunities for sales growth through capital investments. The search for new locations is often placed in the hands of third party real estate brokers who "bring" street corner opportunities to retailers. Some marketers employ their own acquisition staffs who compete with like retailers for increasingly limited available properties.

Staffs ride markets, search county records, work with developers and attempt to network themselves into prosperity by making the right contacts. Once a property is found, retailers often pore over reams of demographic data and review competitors within a two mile radius "trade area" to determine the location's sales potential.

This "inside out" approach (i.e. find a location, then determine its potential) is very inefficient. Retailers should approach site selection as a rigorous process of spotting broad areas of opportunity within and across markets and then seeking specific "hot spots" inside those areas. The process is no different than that of buying a home for your family. You first choose the desirable neighborhoods based on key factors like the quality of school systems, convenience to nearby shopping, recreation areas and other attributes of personal taste. The next step is to narrow down and select a specific house. The neighborhood analogy somewhat oversimplifies the process for store selection but is appropriate for illustration.

MAP VIEW 1 & 2

This article is the second in a five-part series where we will discuss methods to assist marketers in developing a more analytical approach to capital investment decisions. In the first article we outlined the five broad categories of performance (location, facility, price, brand and operations) for convenience retailing and discussed their relative importance in determining sales. This article will focus on illustrating a process for prioritizing market areas using a number of analytical tools and information resources.

Assessing market priorities

Retailers are often faced with determining priorities for their capital investment dollars. Often, in larger corporations, capital allocations are provided on the basis of sales territory geographies or major market areas. Little focus is placed on comparisons of financial returns between stores across markets. Since territories are usually determined by fixed geographic boundaries (e.g. cities, counties) dollar allocation priorities are often misaligned.

Rather, targets for capital investment should be based on the attractiveness of the sales potential of a geographic area that has been defined by the fundamentals of convenience retail performance. There are many approaches to analyzing these fundamentals and ranking areas of high potential. We will describe a methodology that assesses four elements of market attractiveness to determine investment priorities: (1) gaps in supply and demand, (2) quality of competition, (3) growth trends and (4) historical profitability.

MAP VIEW 3

Any solid analytical methodology requires a good source of data. Information for the purposes of this analysis is available from a host of sources. To begin, it is key to obtain detailed data about the competitive environment in the market area. This requires surveying all supply points (stores) in the market area that compete for specific profit center demand. For convenience retailers this means, at a minimum, building a database on gasoline/C-stores and standalone C-stores. There are a limited number of vendors well experienced at supplying this information. New Image Marketing of Fort Meyers, Fla. has been conducting field survey work for marketers for almost 10 years. They generally obtain about 150 variables (physical and subjective characteristics) on each store in a market.

Information about consumers in the market (e.g. demographics, lifestyles, purchase propensities) are also available from a number of vendors (e.g. Claritas, National Decision Systems, etc.) Historical profitability and pricing trends are another important market characterization. Lundberg is often a good source. Broad coverage traffic counts can be obtained from counties, local municipalities or from Business Location Research (BLR) in Tucson, Ariz.

MAP VIEW 4

Obtaining this data does not have to be expensive. There are a few key variables that are most relevant and it is often not necessary to purchase a vendor's entire selection. For example, one of the most overused and least understood series of information is demographics. Most reports contain over 250 variables. We are not sure what marketers do with all of that data; however, we have found about six that are important for convenience retailers (see below).

Look for gaps in supply and demand

The use of off-the-shelf business analysis software is widespread. Specifically, geographic information systems (GIS) software is gaining notoriety as a tool for representing variables spatially. Many retailers use GIS tools to "geo-locate" their stores and construct maps for management reports. However, very few are using these low-cost tools to add rigor to their decision making.

A great application for some GIS products is to spatially represent supply and demand in the convenience retail business. We will use gasoline sales as an example.

Map view 1, represents the location of the gasoline supply sources in a moderate sized county (County A) using a product called SPANS by Tydac Technologies Inc. New Image Marketing conducted the survey and provided an estimate of the gasoline being sold at each unit. The stations are positioned on the map according to their precise latitude and longitude coordinates. These "geo-codes" are obtained on location with a hand held device that acquires a position from the Navy's navigational satellites in earth orbit.

As map view 2 shows, SPANS is then used to construct a surface map of gasoline sales by "bleeding" sales out from each location. As the surfaces from each location overlap and the map is completed, a spatial representation of the supply of gasoline in this market is constructed. On the demand side, an analogous representation is obtained using a database of vehicle counts in the county (map view 3). Other demand variables such as population or household counts could be used.

The final step in the analysis is to overlay the two surfaces to study the geographic areas where gaps between supply and demand exist. In map view 4, an overlay of just the high demand areas classified by the levels of supply is shown. The areas in red depict micro markets where there are very large gaps between supply and demand. Moderate gaps are depicted in orange and very low gaps, or areas where the market is well served, are shown in blue. For greater detail, map view 5 brings up the local road network to aid in the evaluation of individual site candidates located in the high and moderate gap zones.

The power of this tool is not just in the pictorial description of the gap areas but in the quantitative representations as well. This is particularly useful in comparing and ranking markets with one another. For example, an analogous gap map was developed for nearby County B. As the chart above shows, County B has 138 sq.km. (16% of the county land mass) of high and moderate gap areas compared to 88 sq.km. (4% of land mass) for County A.

An analysis of this type could be conducted for any areas under consideration for investment. While this is a great start to the market characterization analysis, it must be complimented by additional work.

Assess the competition

Identifying the gaps between supply and demand are important in locating areas of opportunity. It is equally important to assess the strength of the supply sources and understand how your new or refurbished stores will be positioned relative to them.

There are many elements of a store's characteristics that make it appealing to consumers. The convenience of the location, its appearance, the ease of ingress and egress and product pricing are just a few. A few key variables can also be used to help assess and compare the quality of the stores in aggregate for a given market.

Using our example again of the differences between Counties A and B, Table A shows some marked differences.

A very quick assessment of the differences in these two markets shows that there are vastly more available high gap areas for County B. This difference is amplified by a cursory assessment that the quality of the supply is also much weaker and, therefore, more susceptible to entry. Average appearance scores (subjective assessments by surveyors on a scale of 1 to 6) for both the store and forecourts reveals better curb appeal in County A. G-stores are also smaller (38% have units with greater than 1200 sq.ft. selling space) and less prevalent (57% vs. 74% of service stations have a C-store) in County B. A review of gasoline throughputs also shows a higher amount for County B (68,450 vs. 66,589) potentially signaling that new capacity can be sustained. While this is meant to provide only a cursory look it does show that a distinct difference in the quality of competition for County B warrants additional analysis.

Demand growth

As discussed above, demographic reports can be difficult to analyze. Attempting to determine which variables are relevant and which satisfy anecdotal preconceptions about drivers of performance is not always easy. This is where statistical modeling is helpful. In essence, statistical models are unbiased mathematical representations of consumer and market behavior. In our experience with modeling convenience retail sales, there are six variables that appear to be most significant. Although we do not present them here comparatively for our county examples, these variables are often found to be significant. (See Table B)

A common practice for retailers is to look at demographic variables as a sum or average within a fixed radius since many standardized systems report this way. For our models, we generally weight the terms by distance to a subject site rather than take arithmetic averages. As a result, more weight is given to demand that is closer to the subject location.

Also, it is important to note that our models generally show that these variables are much less important in assessing demand than are traffic counts. Traffic tends to be more influential for gasoline than convenience items. Purely demographic classifications are more useful in assisting marketers to locate target consumer segments. When combined with the host of lifestyle and purchase behavior data available today, models improve in predictive power. All in all, however, quantity of demand outpaces quality.

Profitability

Ultimately, profitability and return on investment must be the benchmarks for decisions on capital investments. It can be difficult to assess the long term profitability of a given location even when sales estimates meet expectations. Product mix influences gross margin and certain market fundamentals affect all stores. For this article we will not discuss the relative importance of product mix for a given store. Rather, focus is placed on the marketplace.

Once a market area has been selected for investment on the basis of supply/demand gaps, competitive landscape and consumer types, it is important to look at variables that influence profitability. A few notable elements are presented in Table C.

Obviously, if you already have stores in the market, your own assessment of historical profitability is appropriate. However, it is important to look at trends in some of the above characteristics to assess the future. For example, if majors are having a more difficult time establishing a margin umbrella, this is a sign that the market is becoming more price competitive and consumers are less tolerant of large differences. In our illustration of the two counties note that the difference in retail prices between majors and independents is 5.5¢/gal. in County A and 1.8¢/gal. in County B. This information is an indication that there is likely a stronger brand influence in "A" than in "B" and that consumers are willing to pay higher prices for a quality offer. It would be equally important to determine the trend over time in these values to spot a change in consumer perceptions and behavior.

In future articles we will discuss the elements of performance for single stores in greater detail. This article defined some of the key elements required in assessing relative market performance. Evaluating gaps in supply and demand, surveying the base of competition, looking at a limited set of demographics and studying some influences of profitability can provide a clearer picture of the attractiveness of one market relative to another. There are certainly other approaches for deciding which markets are attractive for investment. There are also additional elements not discussed in this article that can add clarity. Whatever methodology you choose for determining priorities for capital dollars, a small investment in information and analysis can mean the difference between success and failure.

Guy P. Abramo is managing director for KPMG Resource Planning Consultants. Prior to his current position, he spent 13 years in Mobil Oil's U.S. Marketing Division. He consults with a number of large convenience retail clients and specializes in site selection, store performance analysis and marketing program development. KPMG is at 2001 M St., N.W., Washington D.C. 20036. (202) 467-3000/Fax: (202) 223-2199.

This article was originally published in the March 1997, Issue of National Petroleum News. For information regarding reprints of this or any other Adams publication, click HERE or call (800)396-3939.