Embedded Files
Problem
A local business in Raleigh, NC, is interested in expanding their sales to new customers. They need to know from where (geographically within Wake County) their current customer base is derived in order to consider new marketing schemes in underrepresented areas. This project analyzes existing customer location information to identify areas for new marketing schemes. The business has provided an address database of their customers that will be used to geocode current customer addresses.
Analysis Procedures
The local business provided a Microsoft Excel file containing their customers’ addresses. Additional datasets included Wake County boundary, Wake County streets, and Wake County Zip Code boundary files obtained from Wake County Government GIS. Two separate address locators were generated in ArcCatalog. One address locator used the Wake County streets shapefile as a reference and the other used the Wake County ZIP Code boundary shapefile as a reference. Using ArcMap, the Excel file of customer addresses was geocoded using each address locator. A map displaying the final results was generated for each geocoding process.
All datasets and the Excel file were imported into ArcMap. The attribute tables for each layer and the customer information file were reviewed to determine the most effective address locator. Geocoding proceeded at both the ZIP code and street levels.
For the ZIP code level, I generated an address locator in ArcCatalog using US Address-ZIP 5-Digit style and the ZIP Code boundary shapefile as the reference. I then connected the customer information file to the address locator to proceed with batch geocoding. I reviewed the results for accuracy. Using the US Postal Service ZIP code locator, I determined correct zip codes for unmatched addresses. I produced a map layout of the final results.
For the street level, I generated an address locator in ArcCatalog using US Address – Dual Ranges style and the Wake County streets shapefile as the reference. First, I used the Find function in ArcMap to locate four specific addresses. These addresses were added to the map with a label. I then connected the customer information file to the address locator to proceed with batch geocoding. The fields were inadequate to produce any matched results. I then generated a new field in the customer information table which included both the street number and the street name. I then connected the new customer information table to the address locator for batch geocoding. I reviewed the results for accuracy. I interactively re-matched two addresses. I produced a map layout of the final results.
Workflow diagram (Click to enlarge)
Results
Map displaying zip codes with existing customers (Click to enlarge)
Map displaying customer address locations (Click to enlarge)
Application & Reflection
Geocoding is a useful procedure for identifying locations given a table of addresses. While this particular case focused on the marketing needs of a pre-existing business, other business decisions could benefit from geocoding as well. Specifically, new retail or restaurant entrepreneurs could use geocoding to map competing businesses when searching for a site to locate their business. More appropriate to my area of study though would be to use geocoding to identify locations of grocery stores in determining areas with low food access. Low food access determinations are made based on the locations of grocery stores in impoverished areas. Being more than one mile from a grocery store in an urban, impoverished area results in a low food access designation. I would obtain business location information from Reference USA (available through North Carolina State University GIS library) as well as poverty data at the census block level (available from US Cenus Bureau). The Wake County streets file would be used to geocode the grocery store addresses. Geocoding would be useful to map grocery stores as a first step in making low food access determinations in Wake County.
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