NEW CONCEPTS INTRODUCED AND IMPLEMENTED IN THE APPLICATIONS LECTURES AND LABS.

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1 NEW CONCEPTS INTRODUCED AND IMPLEMENTED IN THE APPLICATIONS LECTURES AND LABS. The three guest lecturers all talked about SITE SELECTION, which is probably the most common technique in business-related GIS. The idea is to pick a location where a proposed business will be most successful, because the local market area contains potential customers who are likely to rent or buy products or services. Examples of how this is done came up in all three labs: 1. In lab 10, the objective of the exercise was to determine which of six available apartment properties offered the best opportunity for investment (i.e. the most likely to pay off with a good return). The best investment opportunities were those that: have limited competition nearby are in or adjacent to good neighborhoods have a large margin between the property s rent and the rent at newer properties surrounding it. 2. Lab 11 had a similar goal to rank 10 available sites in terms of the market potential for a new apartment complex. A predictive model had been built which calculated a site s market potential based on characteristics of the local area. Positive factors were high numbers of nearby business employees and desirable lifestyle households (customers); negative factors were nearby existing and planned competing apartment developments. 3. In lab 12 a site for a new grocery store had to be picked, not from pre-existing sites, but from anywhere in the state of North Carolina. The criteria used to identify the best sites were: population within a 5-mile radius greater than 90,000. at least 10,000 households with an income of $75,000 or more within 5 miles. selected sites must not be within 5 miles of an existing or planned grocery store. to ensure adequate access, a selected site must be on a major road. if more than 3 sites meet the criteria above, selection will be based on the sites with the highest average household income in the surrounding market area. The guest lecturers introduced three new concepts that were then implemented in the lab work to facilitate the site selection process: AIR PHOTO BACKDROPS, GRIDS (Nadine and Deanna) and LIFESTYLE SEGMENTATION DATA (Chris). AIR PHOTO BACKDROPS It is a common practice to make maps with an air photo backdrop; this makes the map more visually appealing than a plain map particularly for non-gis-user clients. Deanna showed some examples of air-photo-based maps with restaurant logos added by Adobe Illustrator or Photoshop. Air photos are also used in the site selection process; for example, in lab 10 an air photo was used to help select good neighborhoods based on desirable and undesirable features nearby a site. Minuses included a landfill or industry nearby, a lack of trees or open

2 space; pluses are lots of trees, tree-lined streets, easy highway access, single-family neighborhood, nearby churches, parks, golf courses, play grounds, schools and retail centers. GRIDS A grid is a layer of (typically) squares that cover a map area. Typically, the grid cells are loaded with socio-economic data aggregated from (typically) census block group data, from within a selected radius from the cell centroid (Figure 1). Figure 1. Section of a grid with square grid cells. For the four highlighted cells, circular buffers are shown, centered on the cell centroids. The buffers are used to aggregate socio-economic data from the local market area. For example, in lab 12 we used pre-made 1-square-mile cells, containing attribute data aggregated from census block group data within a 5-mile radius; the attribute data is representative of the surrounding market area. The utility of the grid is consistent geography - you can select any point on the map and see the characteristics of the surrounding market area. You can also Query Select grids (markets) that meet specified criteria, such as good neighborhoods (lab 10) and high nearby population and household incomes (lab 12). LIFESTYLE SEGMENTATION DATA Every U.S. household can be placed in a lifestyle segment. Segments describe lifestyle, media habits and spending behavior - all of which can help in market research. Examples of Life Style segments...

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4 Segments are based on demographics (e.g. census data) AND psychographics - measures of behavior, habits and lifestyle choices NOT easily obtained from sources of traditional demographics like the Census Bureau; for example, the Census doesn't tell you that someone likes to eat at California Pizza Kitchen or shop at Old Navy. He shops on the Internet and drinks gourmet coffee She shops at specialty stores and watches The Today Show

5 Segmentation data is available from large companies like Experian ( and Claritas ( who collect huge amounts of data via credit card transactions, surveys, competitions, web use and so on. An example of how segmentation data is used can be found in lab 11; households belonging to ten segments (e.g. prosperous metro mix, movers and shakers, urban up and comers etc.) have a propensity to rent (these are potential customers for the new apartment building). The lab includes the total number of these segments in the local area around each site to help calculate market potential.