1 The Use of GIS in Retail Site Selection Analysis GIS 6383 GIS Management and Implementation Fall 2006 Chien-Chou Chen (Joe) Anisha Mandol Gerel Oyun

2 What Is Retail Site Selection? –Selection of new retail location to advance the prosperity and growth of organization –Can be difficult and time consuming –Analysis of variables or factors can be complex

3 General Key Factors to a Potential Site –A large customer base –Proximity to customers –Suitable demographics –High potential market area –High traffic flow (both vehicle and pedestrian) –Close proximity from other amenities –Competitor locations –Reliable sales forecasting

4 How Can GIS Help? –Visualizes, analyzes, and leverages organizational data –Provides spatial analysis of variables –Determines site locations to maximize ROI –Identifies competitive intensity –Avoids cannibalization –Forecasts and models sales –Makes a complex task easy to accomplish and understand.

5 Criteria for GIS Software Selection –The objective of the company –The capability of the software –Technical support and training –The monetary cost of completing the objective (fancy way to say price)

6 Objectives of Company –Locate new outlets –Maximize profits at each new location –Forecast future sales trends –Accomplish objective with minimal cost and optimal accuracy

7 The Capabilities of the GIS Software Spatial data analysis capability –Visualizing –Exploring –Modeling

8 Site Selection Process  Census tracts  Socioeconomic data  Demographic data  Land/zoning  Transportation networks  Location of competitors Competitor analysis Choosing segmentation variables Defining market area Deciding potential outlets Sales forecasting VisualizationExploration Modelin g

9 Visualization Visualizing customer locations is helpful to businesses trying to make better decisions. Analyzing location is key to making decisions about where to set up a business or service. Presenting information as maps reveals relationships and patterns that may otherwise be hidden.

10 Exploration: Retail Spatial Distribution by Using Kernel Density High Competition Area Low Competition Area

11 Exploration: Distribution of Retail Market Penetration by Using Trend-Surface (polynomial function) Technology

12 Exploration : Overlay findings to assist location decision making High Income Family Moderate Retail Density Area 50% Market Penetration Contour Competitors

13 Modeling: Retail Sales Forecasting Multiple Regression Model to predict retail performance of each location Y=a+bX 1 +cX 2 +dX 3 +……X n + Y=retail performance/turnover X 1 =population density in each retail market boundary X 2 =average income in each retail market boundary X 3 =competitor density in each retail market boundary =error term

14 Product Features 1.iSITE integrates demographics, business intelligence and customer data with sophisticated mapping tools. 2.iPREDICT uses custom-drawn digital maps and two modeling techniques-analog and spatial regression-to forecast sales volume and determine benchmarks for selected sites. iXPRESS integrates demographic software, geography software and marketing analysis software tools to conduct retailing location analysis. ArcGIS Business Analysis, an extension to ArcGIS, provides analysis tools, Huff model, and a complete data package, including shopping center data, demographic data, and Centrus Geocoder, to perform sophisticated business analysis.

15 Site Selection Analysis Capability Comparison Site Selection Function iSITE & iPREDICT iXPRESS ArcGIS Business Analyst Visualization Data Mapping geo-referenced feature Exploring Data Competitor analysis Choosing market segmentation variable Defining market area Deciding potential outlets Modeling Data Sales forecasting

16 Technical Support and Training geoVue (iSITE & PREDICT) –provides technical support via telephone and Internet –offers online and on-site training class. Claritas (iXPRESS) –provides toll- free technical support –offers classroom and virtual training, Self-paced training –Internet-based training for one user is available for iXPRESS at no additional cost. ESRI ArcGIS Business Analyst – provides one year of technical support with the initial purchase. – maintenance fees include technical assistance through ESRI's Technical Support Group. – Offers both classroom and online classes.

17 Price Comparison geoVue (iSITE & iPREDICT) –The iSITE package runs between $7,500 - $15,000 –Basic package of iPREDICT starts at $1,995. –Total $16,995 (max) Claritas (iXPRESS) –iXPRESS can cost up to $30,000 –Mapping platform like MapInfo starts at $1,000 –Total $31,000 (max) ESRI (ArcGIS Business Analyst) –The cost of this extension is $18495 –Single use license for ArcView, ArcEditor, or ArcInfo is $1500 –Total $19,995

18 Evaluation Summary iXPRESS Pros –includes an extensive library of data from industry leading data providers –save time in data preparation and conversion –manipulate more complex and customized analysis in visualization and exploration stages Cons –spatial modeling function cannot meet our requirement –needs to be installed in the mapping platform –high cost iSITE & iPREDICT Pros –meet the basic requirements for visualization and exploration analysis for site selection –iSITE provides online model for sharing data across the enterprise –iPREDICT does spatial regression Cons –limited capacity in customized visualization ArcGIS Business Analyst Pros –includes a series of store market analysis tools, like threshold ring and drive time –offers Huff model –combines location referenced information provided by ESRI and Centrus Geocoder to facilitate retail location analysis Cons –costly –Need licenses for ArcView, ArcEditor, or ArcInfo

19 Recommendation Based on evaluation and budget constraints we recommend iSite and iPredict whose –spatial visualizing and exploring capability meet the minimum requirements for market evaluation –two models - analog and spatial regression model for forecasting analysis - provide more choices than Business Analysis’s Huff model for conducting retail forecasting analysis. –software cost is relatively less

20 Reference Bailey, T. C. and A. C. Gatrell 1995 Interactive Spatial Data Analysis. Prentice Hall England. Berry, B. and J. Parr 1988 Market Centers and Retail Location: Theory and Application. Prentice Hall U.S.A. Bronnenberg B.J. and C. Sismeiro 2002 Using multimarket data to predict brand performance in markets for which no or poor data exist. Journal of Marketing Research vol 39 (February): Carter, C and W. Haloupek Spatial Autocorrelation in a Retail Context. International Real Estate Review Vol. 3 No. 1: pp. 34 – 48 Claritas, geoVue, Ghosh, A. and S., McLafferty Location Strategies of Retail and Services Firms, D.C. Heath and Company, U.S.A. Hoover’s Claritas, factsheet.xhtml Hoover’s geoVue Inc, factsheet.xhtml Jansenberger, E. M. and P. Staufer-Steinnocher 2004 Dual Kernel Density Estimation as a Method for Describing. 7th AGILE Conference on Geographic Information Science, Heraklion, secretariat.org/Conference/greece2004/papers/6-2-3_Jansenberger.pdf Stone, J 2005 Beyond Sales Forecasting: Managing Risk in Retail Site Thrall, G. I GIS Applications in Real Estate and Related Industries, Journal of Housing Research 9 (1), Zhou, T Show Me the Location- A GIS Approach on Discount Store Location Study, ESRI User Conference

21 Questions?