8. Site Location

8/11/2019 8. Site Location

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PPT 8-1

5thEdition


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McGraw-Hill/IrwinLevy/Weitz: Retailing Management, 5/e Copyright 2004 by The McGraw-Hill Companies, Inc. All rights reserved.

Site Location

Chapter 8


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Retailing Strategy

Retail LocationsChapter 7

Site LocationsChapter 8

Human ResourceManagement

Chapter 9

Information andDistribution

SystemsChapter 10

CustomerRelationshipManagement

Chapter 11

Retail Market andFinancial Strategy

Chapter 5, 6


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PPT 8-4

Location Chapters

Chapter 7

General Description of the Location Types

Advantages and Disadvantages of Different Location

AppendixTerms and Condition Involved in LeasingSites

Chapter 8

Considerations in Selecting Area for Locating Store

Issues in Evaluating Specific Sites


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Three Levels of Analysis


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Trade Area Issues

Which Trade Areas Are Most Attractive forLocating Retail Outlets?

How Many Outlets to Locate in a Trade Area? More Stores Increases Economies of Scale and

Reduces Costs

More Stores also Results in More Cannibalizationand Less Sales per Store


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Factors Affecting Demandfor a Region or Trade Area


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Factors Affecting theAttractiveness of a Site

How Attractive Is the Site to the RetailersTarget Market?

Match Between Trade Area Demographics and

Retailers Target Market Likelihood of Customers Coming to Location

Convenience

Other Attractive Retailers At LocationPrinciple of cumulative attraction- a cluster of similar

and complementary retailing activities will have greaterdrawing power.


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Convenience of Going to Site

Accessibility

Road pattern and condition

Natural and artificial barriers

Visibility

Traffic flow

Parking

Congestion

Ingress/egress


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In High Traffic Areas

Near Anchor

Center of Shopping Area Near Stores Selling Complementary

Merchandise

Clustering Specialty Stores Appealing toTeenagers

Better locations cost more

Location Within a Center


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Map of Dallas North Park Center


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Estimating Demand for a New Location

Definition of the Trade Area

Primary, Secondary, Tertiary Zones

Approaches for Estimating Demand

Analog Approach

Regression Approach

Huff Gravity Model


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Trade Area

Primary zone- 60 to 65 percent of its customers

Secondary zone- 20 percent of a stores sales

Tertiary zone- customers who occasionally shopat the store or shopping center


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Factors Defining Trade Areas

Accessibility

Natural & Physical Barriers

Type of Shopping Area

Type of Store

Competition

Parasite Stores


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Oblong Trade Area Caused byMajor Highways and Natural Boundaries


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Sources of Information

Customer Spotting

Census Data

Geodemographic InformationSystems

ACORN

Information on Competition

Yellow Pages


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Customer Spotting

Purpose: to spot, or locate, the residences ofcustomers for a store or shopping center.

How to obtain data:credit card or checks

customer loyalty programs

manually as part of the checkout process

automobile license plates


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Census Data of the U.S.

.

Only once in 10 years.

Each household in the country iscounted to determine the numberof persons per household,household relationships, sex, raceage and marital status.


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Geodemographic Information Systems

Demographic data vendorsspecialize inrepackaging and updating census-type data.

Geographic Information System(GIS) is a

computer system that enables analysts tovisualize information about their customersdemographics, buying behavior, and other data ina map format.

GIS is a spatial database that stores the location andshape of information.

Analysts can identify the boundaries of a trade areaand isolate target customer groups


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Indices for Assessing Sales Potential

Market Potential Index (MPI)

Number of Households Purchasing a Product orService in a Trade Area

Spending Potential Index (SPI)

Average Amount Spent on a Product or Service by aHousehold in a Trade Area


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Sources for Measuring Competition

The Internet- lists current locations and futuresites.

Yellow Pages

Other Sources: Directories published by tradeassociations, chambers of commerce, ChainStore Guide, International Council of Shopping

Centers, Urban Land Institute, local newspaperadvertising departments, municipal and countygovernments, specialized trade magazines, listbrokers


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Measuring Competition

Calculate total square footage of retail space

devoted to a type of store per household

Higher ratios will indicate higher levels of

competition

C titi A l i f


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Competitive Analysis forEdward Breiner


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Methods for Estimating Demand

Analog Approach

Multiple Regression Analysis

Huffs Model


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The Analog Approach

1. Current trade area is determined by using thecustomer spotting technique.

2. Based on the density of customers from the store, theprimary, secondary and tertiary trade area zones aredefined.

3. Match the characteristics of our current store with thepotential new stores locations to determine the best

site.

3 Steps:

I Di ib i f Th Mil


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Income Distribution of Three-MileRing Surrounding Edward Breiner Optical

D hi T d f Th Mil


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Demographic Trends for Three-MileRing Surrounding Edward Breiner Optical


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ACORN Neighborhood Lifestyle Clustersfor Three-Mile Ring

Breiner Optical

D i ti f L t PRIZM


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Descriptions of Largest PRIZMClusters Surrounding Edward Breiner Optical


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Description of Largest PRIZMClusters Surrounding Edward Breiner Optical

D i ti f L t PRIZM


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D i ti f L t PRIZM


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D i ti f Ed d B i O ti l


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Descriptions of Edward Breiner Opticaland Four Potential Locations Trade Areas


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Multiple Regression Analysis

Need to define the retail trade area potentialfor retail chains with greater than 20 stores.

Similar to the analog approach, it usesstatistics rather than judgement to predictsales for a new store.


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Multiple Regression Steps

Current trade areas are determined by usingthe customer spotting technique

Primary, secondary, and tertiary zones aredetermined by plotting customers on a map

Select appropriate measures ofperformance, such as per capita sales ormarket share.

Select a set of variables that may be usefulin predicting performance.

Solve the regression equation and use it toproject performance for future sites.

Yearly Sales Population and


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Yearly Sales, Population, andIncome for 10 Home Improvement Centers


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Regression of Population on Sales


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Illustration of Regression Approach

1. Specify Regression ModelIdentify Critical Predictorsof Store Sales

Sales = B0+ B1x X1+ B2x X2

X1 = population in trade area

X2 = average household income in tradearea

2. Estimate Weights - B0,B1, B2

3. Use Estimated Weights to Forecast salesSales = -144,146 + 6,937 x X1+ 10,132 x X2

Sales = -144,146 + 6,937 x 55,000 + 10,132 x 28,000 = $521,085


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Huffs Gravity Model

Based on the premise that the probability that agiven customer will shop in a particular store

or shopping center becomes larger as the size

of store or center grows and distance ortravel time from customer shrinks


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Huffs Model Formula

tripsshoppingofkinds

differentontimetravelofeffectthereflectsthatoexponent tAn

center

shoppingpoint tostartingscustomer'fromdistanceortimeTravel

centershoppingofSize

centershoppingparticular

atotravelingoriginofpointgivenaatcustomeraofyProbabilit

Where

ijTb

ijT

jj S

j

iijP

n

1j

bijTjS

bijTjSijP

University and Shopping Centers:


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University and Shopping Centers:Gravity Model Illustration


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Huffs Model: The Solution

Pi j = 1000 32

(1000 32) + (500 52) + (100 12)

Probability = .48

.48 x 12,000 students = 5,760 customers

5,760 customers x $150 = $864,000

Repeat steps 1 to 3 for the remaining areasand then sum them.

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8. Site Location