Geocoding for Market Research



The goal of this project was to illustrate how Geocoding can be used in Market Research based upon the following scenario:
A local event sponsor in Raleigh, NC puts on an art show exhibition in the downtown area every year to showcase the work of local artists. The Wake County government has agreed to continually provide support for this event, as long as he function provides an attraction for its citizens throughout the County. To ensure effective planning for future shows, the sponsors have requested an analysis to determine where their program's attendees come from and to make recommendations for effective market reach in areas of the county that are less well represented.


This project was part of the requirements for GIS 520, Advanced Spatial Analytics. The data was provided with the assignment and consisted of shapefiles for Wake County's boundary, zip codes, and major streets. An excel spreadsheet was also provided that contained date representing data collected from the previous year's attendee list.


This exercise demonstrated geocoding from two perspectives. The first was at the zip code level and provided a broad view of where the attendees originated. This approach is useful to show a high-level distribution of attendees throughout the county, but lacks the detail needed for effective decision making. The drawback of this method, is that it is not possible to determine the number of attendees from each zip code, only if a zip had attendees from last years event.

The second analysis was performed at the street level, and provided a detailed view of where each attendee originated. By geocoding to the street level, each attendee is uniquely represented by a single address. This method better illustrates the true distribution of attendees throughout the county and can provide more accurate results to the Wake County Government for making decisions on supporting the event in the future.

Ideally, both analysis would be used together to provide a complete picture of last years participant distribution.


Geocoding allows the spatial analysis of data that normally is only available in non-spatial a non-spatial format. This technique is very valuable when studying non-spatial events and the geographical relationship of them to surrounding entities. The ability to visualize distributions and clustering of data on a map can quickly reveal patterns that may not be possible to determine from raw tabular data.