1. Potential Markets for South Carolina- SPC Direct
Researcher: Johnnie German
Instructors: Ryan Schuermann and Ioannis Kamarinas
Geographic Question
Where are the best areas to generate new business in South Carolina? Where is their market
distribution across South Carolina? What is the distribution of insured populations across South
Carolina? What is the distribution of households and mean income in South Carolina?
Background
SPC Direct is a marketing company that specializes in the promotion and sales of
personalized compounded medications. They have established markets across the United
States. Their goal is to serve the community through ethical, honest, and highly trained
representatives for the compounding pharmaceutical industry. SPC Direct currently has 21
doctors who are using their services in South Carolina. The goal of this project is to evaluate the
market potential of new areas.
This project will present SPC Direct’s market shares within South Carolina. It will
investigate the potential for areas outside of their current market share by comparing county
income, healthcare census data, and a 40,000 city population. This analysis will show the
counties that meet this criteria. SPC Direct’s current market strategy was not a factor in this
analysis. It was mutually agreed that a lack of knowledge of their current marketing strategies
would help evaluate their existing marketing approach and to limit any bias on this analysis.
Data
The data sets for the market share in South Carolina came from SPC Direct in an Excel
spreadsheet. This spreadsheet contains columns with the doctor’s name, doctor’s address,
gross insurance revenue, and prescription information—medication type, amount, and dates
(Cable 2014). The data set includes information collected by SPC Direct from October 2013 to
May 2014. The data represents sales information from prescribing medical providers. National
Provider Identifier (NPI) numbers were extracted from bloom.api.com and added to the
spreadsheet in order to categorize the doctors by a unique identifier instead of their name
(Wasser n.d.). The NPI numbers allow revenue amounts to be displayed by doctor in Arc GIS by
summery of revenue and eliminate any duplicate or identical name variations or misspellings.
There were seven out of the twenty one doctors that did not have a validated NPI number, and
were subsequently given a value of zero.
Two population data sets were collected from the United States Census Bureau website
at AmericanFactFinder.com. These data sets consist of population insured rates and mean
income by household for all counties in South Carolina. These data sets include a three year

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estimate and range from January 1, 2011 to December 31, 2014 with populations of 20,000 or
more. These surveys were prepared by American Community Survey (United States Census
Bureau n.d.). The three year range was chosen for estimate growth over a period of time
instead of one year.
Several geographic files or shapfiles were used in this project. These files consist of a
South Carolina county shapefile, a five digit zip code tabulator, and a South Carolina cities
shapefile. All shapefiles are projected in Universal Transverse Mercator North American Datum
1983 Zone 17N. The county shapefile was obtained from the South Carolina Department of
Natural Resources website, and was created by the United States Geological Survey in 2013
(United States Geological Services 2013). The five digit zip code tabulator was obtained from
the United States Census Bureau website within the Geography page. The tabulator was
created in 2013 and uses North American Datum 1983 with no zone (United States Census
Bureau 2013). The South Carolina cities shapefile came from the University of South Carolina
website on the Campus GIS page, and was created by the American Community Survey in 2006
(American Community Survey 2006).
Methods of Analysis
The first step completed in this analysis involved editing and formatting the Excel
spreadsheets received from the United States Census Bureau and from SPC Direct. These
spreadsheets were modified for use in the geographic software Arc GIS by ESRI, Inc. Once the
tables were formatted and edited, they were joined with the counties shapefile to show their
distributions geographically.
The first created map demonstrates the market distribution of SPC Direct in South
Carolina from October 2013 to May 2014. The Excel spreadsheet was geocoded using the five
digit zip code tabulator. Once geocoded, the doctor’s addresses are displayed geographically in
the form of points. A summary operation was performed on the NPI number column. This
operation was executed to distribute the gross revenue by doctor’s address. The NPI number
serves as a unique identifier and allows for multiple duplicate entries such as a doctor’s name.
It also avoids the problem of points on top of points geographically and distributes the values in
the gross insurance revenue fields to one location. In this case, that location is the doctor’s
address. This map was created by joining the SPC market share spreadsheet with South Carolina
county shapefiles. A graduated colors map containing the gross insurance revenue by doctor
address and the South Carolina counties displays SPC Direct’s market distribution in South
Carolina.
SPC Direct requested a map showing their market results compared to urban city areas.
The United States Census Bureau defines an urban area as a population of 50,000 or more
(United States Census Bureau 2010) . A second map was created to show the market
distribution and cities with a population of 40,000 or more. The cities shapefile was generated
in 2006. To account for progressive population growth, cities with a population of 40,000 have

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been selected to reflect an estimated growth rate of one percent per year (United States
Census Bureau 2005). This map was created by joining the SPC market share spreadsheet with
the counties shapefile. In addition to the counties shapefile, a city layer was added to display
cities containing a population of 40,000 or more.
Two unique values maps were generated using the healthcare and mean income census
data sets. These maps were produced by joining the healthcare and insurance census data to
the county shapefile individually. The gray areas, located on the unique values maps, represent
population areas in which data is absent. Furthermore, these gray areas are counties which
contain a population less than 20,000 and were not surveyed (United States Census Bureau
n.d.).
A close look at the attribute table for the household population shows forty counties
with data, and seven without data. The seven without data were not surveyed due to a
population of less than 20,000 (United States Census Bureau n.d.) The forty counties with data
were selected. After performing a statistics function, descriptive statistics are produced with a
mean of 42,183, a maximum of 175,963, and a minimum of 7,018. The mean household income
for this project was rounded down to 40,000. It was rounded to accommodate for those
counties close to 40,000.
Mean income, or middle class, can be an ambiguous term. An article from U.S. News
and World Report states, “Robert Reich, a professor of Public Policy at the University of
California-Berkeley and former Secretary of Labor, has suggested the middle class be defined as
households making 50 percent higher and lower than the median, which would mean the
average middle class annual income is $25,500 to $76,500” (Williams 2014). The United States
Department of Commerce Economics and Statistics Administration defines the minimum yearly
income for a typical middle class family as $50,800 per year (United States Department Of
Commerce: Economics and Statistics Administration 2010, 2). Therefore, the mean income for
the analysis of this project is $50,000.
After producing the unique values maps for healthcare insurance and mean income, two
selected attribute maps were generated. This was accomplished by selecting by attributes for
counties that contain a healthcare insured population of 40,000 or more from the healthcare
insurance population table. An additional selection was made from the mean income table to
show counties with a 40,000 or more household population and a $50,000 or more mean
income population.
Once the selected features maps were generated, an intersect overlay was performed
on the health insurance and mean income maps. The resulting map displays counties that meet
both of these criteria. A market share layer was added to this map to define where the current
market share intersects with the potential market areas. Next, the counties that already have
market presence were selected. Those counties were exported to a new layer. Both known and
unknown potential market shares are drawn along with the county layer. The resulting map

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illustrates the potential markets for SPC Direct including and excluding their known market
share.
To illustrate the potential market areas, a layer was added that displays cities with a
population of 40,000 or more. These will become the newly discovered potential high value
target areas. The resulting map displays the high value market area in York County and the city
of Rock Hill. A detailed analysis of the potential market areas is discussed in the conclusion of
this report.
Results
The preceeding maps show the results of the methodology of this project. The first map,
SPC Direct Market Share South Carolina, is a graduated colors map displaying SPC Direct’s
market share by doctor’s address and distributes each doctor’s gross insurance revenue. The
second map, SPC Direct Market Share South Carolina & Cities With Population of 40,000 and
Up, is a graduated colors map displaying SPC Direct’s market share by doctor’s address and
distributes each doctor’s gross insurace revenue . Furthermore, this map illustrates cities with a
population of 40,000 and up.
Map number three, Health Insurance Population South Carolina 3 Year Estimate, is a
unique values map displaying the healthcare populations by county from the 2014 three year
census estimates. Map four, Mean Income by Household South Carolina 3 Year Estimate, is a
unique values map displaying the mean income and household populations by county from the
2014 three year census estimates.
The fith map, South Carolina Counties With Healthcare Population 40,000 and Up, is a
selected attributes map that displays the counties that have healthcare insurance populations
of 40,000 and up. The data on this map was selected from map number three. Map number six,
South Carolina Counties With Mean Income of $50,000 and Up & Household Population of
40,000 and Up, is a selected attributes map that displays the counties that have a mean income
of $50,000 and up with a household population of 40,000 and up. The data on this map was
selected from map number four located on page eight of this report.
The seventh map, Potential Markets South Carolina, is a selected attributes map that
displays the intersect of map five and map six. This map, located on page eleven of this report,
illustrates the counties that meet both criteria in maps five and six. These counties represent
the valued markets for SPC Direct. They include their current market share. The final map,
Potential Markets High Value Area, is a selected attributes map that displays the same
characteristics as map seven. However, this map highlights the high value area of York County
and the city of Rock Hill. This map is on page twelve of this report.

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Conclusion
In summary, this analysis demonstrates the best potential markets in South Carolina for
SPC Direct. Furthermore, it clarifies the physical location of their current market and the
distribution of income and health insurance status in these localities. The market distribution
maps show where SPC Direct’s market share is located by county and which counties have a city
with a population of 40,000 or more. In addition to the location of their markets, these maps
also show the distribution of gross insurance revenue by doctor’s address. Moreover, the gross
revenue distribution allows SPC Direct to evaluate the quantity of revenue produced by each
doctor.
The healthcare insurance and mean income by household unique values maps illustrate
the county populations of these conditions. The selected attribute maps, containing
household/mean income populations and healthcare insurance populations, demonstrates the
selected market criteria for South Carolina. When combining the selected attributes by
intersect overlay, the output is the potential market areas. The counties with market potential
that were uncovered by the analysis include: Greenville, Lexington, Richland, Beaufort,
Charleston, Dorchester, Berkeley, Florence, Horry, York, Spartanburg, Pickens, and Anderson
counties. Greenville, Lexington, Richland, Beaufort, and Charleston counties currently have a
SPC Direct market presence. Therefore, the counties without market share are Dorchester,
Berkeley, Florence, Horry, York, Spartanburg, Pickens, and Anderson.
Five counties without market share are adjacent to counties that currently have market
share with SPC Direct. For example, Greenville County splits Pickens and Anderson Counties on
the western side and Spartanburg on the eastern side. Moreover, the city of Greenville is
located in Greenville County with a population of 56,000. Pickens, Anderson, and Spartanburg
counties should be investigated further for future business potential. The areas near the
county lines and the outer edge of the city of Greenville hold the most promise for additional
revenue. However, additional analysis of these areas is needed to fully evaluate their potential.
Dorchester and Berkeley counties (no market share) are adjacent to Charleston County
(market share). Charleston County also contains the cities of Charleston-population 96,650,
North Charleston- population 79,641, and Pleasant- population 47,608. The urban areas that
expand into Dorchester and Berkeley counties should be investigated first and then expand
outward away from the cities of Charleston, North Charleston, and Pleasant.
The remaining counties of York, Florence, and Horry were evaluated individually during
this analysis. Florence County has a household population of 50,923, a mean income of
$57,982, and a healthcare insurance population of 116,547. However, this county does not
contain a city with a population of 40,000 or more. Horry County has a household population of
113,954, a mean income of $54,340, and a healthcare insurance population of 217,285. This
county also does not have a city with a population of 40,000 or more. York County has a
household population of 87,303, a mean income of $70,610, and a healthcare insurance

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population of 201,317. This promising location contains the city of Rock Hill with a population
of 49,765.
The output of this analysis reveals that York County has the highest market potential in
the state of South Carolina. It is recommended that SPC Direct investigate York County. This
decision is due to York County’s the high income rate, a city with 40,000 plus population, and an
insured population of approximately 200,000. The second area with the most potential based
on the criteria of this analysis is Horry County. Florence County is last on the list of potential
market areas due to lower income and healthcare insurance populations.

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