Using GIS to Understand Retail Customers Subir Bandyopadhyay Joe Ferrandino Professor of MarketingAssistant Professor of Criminal Justice Indiana University Northwest Indiana GIS Conference Indianapolis May 7-8, 2014

Introduction GIS maps have been used in marketing for several applications —Retail site location —Coupon optimization —Sentiment analysis —Billboard advertising —Real estate appraisal

GIS and Economic Development Cities and regions can identify suitable locations to attract investment from different industries Combine national and commercially available databases with local proprietory databases to refine location analytics

Integration of Data Sources US Census Bureau (block group data) Indiana Map (parcel data, interstate ramps) City of Gary (existing business locations) Business Analyst ® (Health Spending Index) Gary Police Department (homicide and shooting event data) INDOT (traffic counts) These types of files are available, but many smaller firms or businesses may not technology or expertise to utilize them

Supermarket Location Parameters A mid-sized supermarket chain would like to open a new outlet in Gary, Indiana. The chain typically uses the following location criteria: ― It should be within 1 mile of an exit from an Interstate. ―The site must sit on a road with an average 500/car per hour traffic volume ―There should be no other competition within 0.5 miles from the proposed location ―The average income should be $30 K or more in the area within 1 mile radius of the proposed location, ―The population should be 5,000 or more in the area within 1 mile radius of the proposed location. ―The annual shooting incidents should be 10 or less in the area within 1 mile radius of the proposed location.

Step 1: All city parcels, streets and existing grocery store locations

Step 2: Identification of all parcels within 1 mile of interstate ramps

Step 2: Parcels within 1 mile of interstate

Step 3: Identify roads with an average traffic volume of at least 500 cars/hour

Step 3: Identify remaining parcels on roads with desired traffic volume

Step 4: Create 0.5 Mile Competition Buffers

Step 4: Identify remaining parcels that meet competition criteria

Step 5: Exclude parcels with existing businesses

Step 6: Remaining parcels after public safety and demographic criteria included

Pharmacy Location Parameters A national drug store chain would like to open a new store in Gary, IN. The chain selects a new location if it satisfies the following criteria: ―It should be on a state high road with traffic movement rate of 500 cars or more in a hour from 9am to 9 pm. ―There should not be more than 1 drugstore within 1 mile radius area around the proposed location. ―The annual shooting incidents should be 5 or less in the area within 1 mile radius of the proposed location. ― The population should be 1,000 or more in the area within 1 mile radius of the proposed location. ―The area should have a high senior population ―The area should have a high health spending index score

Step 1: All parcels, streets and existing pharmacies

Step 2: Identification of roads with an average daily traffic volume of 500 cars/hour

Step 2: Identify remaining parcels on roads/streets meeting traffic criteria

Step 3: Buffer/Intersect utilization to eliminate parcels with more than 1 pharmacy within 1 mile

Step 4: Eliminate remaining parcels with existing business

Step 5: Remaining parcels after safety data (homicides and shootings) taken into account

Step 6: Identification of potential location areas for market demographic analysis (senior population) within 1 mile

Step 7: Comparative site location parameters for final decision making

Implications for Business More accurate location analytics by incorporating local databases (e.g., crime data, traffic data etc.) in the decision mix

Implications for Local Government Identify suitable locations for different businesses within the city as a prerequisite to attempts to attract business (proactive and data-driven economic development) Help in decisions to develop areas for potential investments (creating attractive sites and understand why some areas are underdeveloped) Make professional presentation to potential investors (make data available, in GIS formats, for any potential business owner or entrepreneur)

Concluding Comments Regional and City administrations have limited human resources to carry out location analytics outlined here Potential for active collaboration between universities and cities in business location analytics Similar collaboration already happens in the field of crime analysis in Northwest Indiana