8. Análise das áreas de
influência
Objectives
8.1 To demonstrate the importance of store location for a
retailer and to outline the process of choosing a store
location
8.2 To discuss the concept of a trading-area and its related
components
8.3 To show how trading-areas may be delineated for
existing and new stores
8.4 To examine three major factors: population
characteristics, economic base characteristics, and
competition/level of saturation
Location, Location, Location
• Criteria to consider include
– population size and traits
– competition
– transportation access
– parking availability
– nature of nearby stores
– property costs
– length of agreement
– legal restrictions
Choosing a Store Location
Step 1: Evaluate alternate geographic (trading) areas in
terms of residents and existing retailers
Step 2: Determine whether to locate as an isolated store or
in a planned shopping center
Step 3: Select the location type
Step 4: Analyze alternate sites contained in the specific
retail location type
Trading-Area Analysis
A trading-area is a geographic area containing the
customers of a particular firm or group of firms for
specific goods or services.
Benefits of Trading-Area Analysis
• Discovery of consumer
• Assessment of effects of
demographics and
trading area overlap
socioeconomic characteristics
• Ascertain whether chain’s
• Opportunity to determine
competitors will open nearby
focus of promotional activities
• Discovery of ideal number of
• Opportunity to view media
outlets, geographic
coverage patterns
weaknesses
• Review of other issues (e.g.
transportation)
Figure 8.2 The Trading-Areas of Current
and Proposed Outlets
GIS Software
• Geographic Information Systems
– Digitized mapping with key location-specific data used
to graphically depict trading-area characteristics such
as
▪ population demographics
▪ data on customer purchases
▪ listings of current, proposed, and competitor
locations
Figure 8.3(A) GIS Software in Action (A chain retailer could learn which of its stores
have trading areas with households having a median annual income of more than $50,000. That firm
could derive the sales potential of proposed new store locations and their potential effect on sales at
existing stores. It could also use software to learn the demographics of customers at its best locations
and set up a computer model to find potential locations with the most desired attributes. A retailer
could even use the software to pinpoint its geographic areas of strength and weakness.
Figure 8.3(B) GIS Software in Action
Figure 8.3(C) GIS Software in Action
Figure 8.3(D) GIS Software in Action
Retail Trade Area Visualization Tool
Please click URL to view:
https://youtu.be/qPszDQ9g7GA
Figure 8.4 The Segments of a Trading
Area
The Size and Shape of Trading-Areas
• Primary trading-area
– 50-80% of a store’s customers
• Secondary trading-area
– 15-25% of a store’s customers
• Fringe (border) trading-area
– all remaining customers
Destination Versus Parasite Stores
• Destination stores have a
better assortment, promotion,
and image.
• Parasite stores do not create
their own traffic and have no
real trading-area of their own.
• They generate trading-areas • These stores depend on
much larger than competitors.
people who are drawn to area
for other reasons.
• Dunkin’ Donuts: “It’s worth
• Magazine stand in office
the trip!”
building
Trading Areas and Store Types
Delineating Trading-Area of an Existing
Store
• Multiple data sources must be used: Secondary data:
– Store records (cash, credit customers)
– Purchase frequency, ticket amount, geographic
location
• Primary data:
– Patronage, traffic patterns
– Demographic & lifestyle info (PRIZM)(now owned by
Nielsen)
The Trading-Area of a New Store
• Different tools must be used when an area is evaluated in
terms of opportunities rather than current patronage and
traffic patterns:
– Trend analysis
– Consumer surveys
– Computerized trading-area analysis models
Computerized Trading-Area Analysis
Models
• Analog Model-Potential sales for a new store are estimated on the
basis of revenues for similar stores in existing areas, the competition at
a prospective location, the new store’s expected market share at that
location, and the size and density of the location’s primary trading area.
• Regression Model-Uses a series of mathematical equations
showing the association between potential store sales and several
independent variables at each location, such as population size,
average income, the number of households, nearby competitors,
transportation barriers, and traffic patterns.
• Gravity Model
Analog, Regression and Gravity Models
• Analog models– simplest. Revenue estimates based on
similar stores, competition, expected market share, size
and population density
• Regression models- looks at population size, average
income, transportation barriers and traffic patterns
• Gravity models– looks at distance and shopping selection
at given location
Reilly’s Law (1 of 2)
Reilly’s law of retail gravitation—a traditional means of
trading-area delineation—establishes a point of
indifference between two cities or communities so that
the trading-area of each can be determined.
The point of indifference is the geographic breaking
point between two cities (communities) at which
consumers are indifferent to shopping at either.
Reilly’s Law (2 of 2)
Dab 
Dab =
d
=
Pa =
Pb =
d
Pb
1
Pa
Limit of city (community) A’s trading area, measured in
miles along the road to city (community) B
Distance in miles along a major roadway between cities
(communities) A and B
Population of city (community) A
Population of city (community) B
Exercise: Reilly’s Law
Cities A and B are 50 miles apart. City A has a population of
400,000 and City B has a population of 100,000. According
to Reilly's law, what is the point of indifference for City B?
Calculation: Reilly’s Law
Dab 
50 miles
100,000
1+
400,000
Point of indifference for City B = 16.7 miles
Exercise Solution: Reilly’s Law
•
Dab 
50
1.5
, i.e., 16.7 miles from smaller city and 33.3 miles
from larger city Indifference point
• Assumes that larger city has more retail facilities and
greater drawing power as a result
• Assumes that road conditions, congestion, driving
conditions are equal in both cities
Limitations of Reilly’s Law
• Distance is only measured by major thoroughfares (routes);
some people will travel shorter distances along cross
streets.
• Travel time does not reflect distance traveled. Many people
are more concerned with time traveled than with distance.
• Actual distance may not correspond with perceptions of
distance.
Huff’s Law
Huff’s law of shopper attraction delineates trading-areas on
the basis of product assortment at various shopping
locations, travel times from the shopper’s home to alternative
locations, and the sensitivity of the kind of shopping to travel
time.
Exercise: Huff’s Law
Use Huff’s law to compute the probability of consumers’
traveling from their homes to each of three shopping areas:
square footage of selling space—Location 1, 15,000;
Location 2, 20,000; Location 3, 25,000; travel time—to
Location 1, 15 minutes; to Location 2, 21 minutes; to
Location 3, 25 minutes; effect of travel time on shopping
trip—2
Solution: Huff’s Law
(15,000)/(15)2
pil =
= 43.9%
2
2
2
(15,000)/(15) + (20,000)/(21) + (25.000)/(25)
(20,000)/(21)2
pil =
= 29.8%
2
2
2
(15,000)/(15) + (20,000)/(21) + (25.000)/(25)
(25,000)/(25)2
pil =
= 26.3%
2
2
2
(15,000)/(15) + (20,000)/(21) + (25.000)/(25)
• The probabilities of consumers, traveling to locations 1, 2, and
are 43.9 percent, and 26.3percent, respectively.
Elements in Trading-Area Selection
• Population Characteristics
• Economic Base Characteristics
• Nature and Saturation of Competition
Table 8.1a Chief Factors to Consider in
Evaluating Retail Trading-Areas
Population Size and Characteristics
• Total size and density
• Age distribution
• Average educational level
• Percentage of residents owning homes
• Total disposable income
• Per-capita disposable income
• Occupation distribution
• Trends
Comparing Multiple Retail Sites
URL: https://youtu.be/urvTaXUFH9E
7:46 mins.
How Do I Compare Multiple Areas for Retail Site
Selection
Table 8.1b Chief Factors to Consider in
Evaluating Retail Trading-Areas
Availability of Labor
• Management
• Management trainees
• Clerical
Table 8.1c Chief Factors to Consider in
Evaluating Retail Trading-Areas
Closeness to Sources of Supply
• Delivery costs
• Timeliness
• Number of manufacturers
• Number of wholesalers
• Availability of product lines
• Reliability of product lines
Table 8.1d Chief Factors to Consider in
Evaluating Retail Trading-Areas
Economic Base
• Dominant industry
• Extent of diversification
• Growth projections
• Freedom from economic and seasonal fluctuations
• Availability of credit and financial facilities
Table 8.1e Chief Factors to Consider in
Evaluating Retail Trading-Areas
Competitive Situation
• Number and size of existing competition
• Evaluation of competitor strengths and weaknesses
• Short- and long-run outlook
• Level of saturation
Table 8.1f Chief Factors to Consider in
Evaluating Retail Trading-Areas
Availability of Store Locations
• Number and type of store locations
• Access to transportation
• Owning versus leasing opportunities
• Zoning restrictions
• Costs
Table 8.1g Chief Factors to Consider in
Evaluating Retail Trading-Areas
Regulations
• Taxes
• Licensing
• Operations
• Minimum wages
• Zoning
Table 8-3 Selected 2010 Population Statistics for Long
Beach Trading-Areas A and B (4164 and 4166) (4167.01
and 4168)
Total population, 2010
12,532
Population change 2000-2010 (%)
-8.7
-5.7
College graduates 12 and older,
2010 (%)
48.2
48.9
Median household income, 2010
$94,778
$98,317
Managerial and professional
specialty occupations (% of
employed persons 16 and older),
2010
47.1
10,430
51.5
Trading Area Saturation Indices
• Number of persons per retail establishment
• Average sales per retail store
• Average sales per capita
• Average sales per square foot of selling area
• Average sales per employee
• Saturated, oversaturated and under saturated conditions