Retail Location Strategy

Presented by: Saptarshi BagchiSubmitted to: Mr. Tapas Bhattacharya

Roll-05, FMS-1, NIFT, Kolkata

Objective

• To understand the importance of Retail Location

• To identify and gauge the importance of factors influencing choice of retail location

• To understand the practical implementation of the theory

Importance of Retail Location

Retail Site Selection is a very strategic decision. •Once a location is chosen, a retailer must live with it for many years. •The difference between moving into a superior trade area and one that isn’t, can mean the difference between a successful store and a failure.•Furthurmore, even if a retailer finds the right neighbourhood, the wrong site can spell disaster.

Factors affecting the demand for a region or

trade area

•Economies of Scale versus Cannibalization•Demographic and Lifestyle Characteristics•Business Climate•Competition•Span of Managerial control•Global location issues

Economies of Scale vs Cannibalization•Promotion and Distribution network support

•Best Number of stores in an area

Demographic & Lifestyle Characteristics

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•Population growth•Household income•Size and composition of household•Education level•Lifestyle

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Business Climate•Market’s employment trend•Economy growth and sustainability•Diversified growth of industries

Competition•Saturated trade area•Understored trade area

Span of Managerial Control•Regional geographic orientation

•Regional market orientation

Global Location issues•Foreign location issues•Costs – occupancy cost, rental cost•Legal restrictions•Lack of right knowledge

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Factors affecting the attractiveness of a site

•Accessibility•Locational advantage within a centre

Accessability

Macro analysis•Road patterns•Road conditions•Natural & Artifical barriers

•Micro analysis•Visibility•Parking•Traffic flow•Congestion•Ingress/Egress

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Locational advantage within a centre

•Importance of superior/costly locations•Proximity to supermarket/department store•Principle of cumulative attraction

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Estimating demand for a new location

•Trade Area•Sources of information•Methods of estimating demand

Trade Area

•Primary zone (60%-65% customers)•Secondary zone (20% store sales)•Tertiary zone (Occasional customers)• Lack adequate retail facilities closer to home• Excellent communication system to reach store• Drive near store on the way to/from work• Store is located near a tourist area

•A trade area is a contiguous geographic area that accounts for the majority of store’s sales and customers

Factors defining trade areas

•Store’s accessibility•Natural and physical boundaries•Type of shopping area•Type of store•Competition

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Typical Size & Trading Area of Shopping Centers

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Type of Shopping Center Neighborhood

Gross Leasable Square Feet 30,000 to 150,000

Primary Trade Area 3 Miles

Typical Size & Trading Area of Shopping Centers

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Type of Shopping Center Community

Gross Leasable Square Feet 100,000 to 350,000

Primary Trade Area 3-6 Miles

Typical Size & Trading Area of Shopping Centers

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Type of Shopping Center Regional

Gross Leasable Square Feet 400,000 to 800,000

Primary Trade Area 5-15 Miles

Typical Size & Trading Area of Shopping Centers

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Type of Shopping Center Super-Regional

Gross Leasable Square Feet 800,000 & more

Primary Trade Area 5-25 Miles

Sources of information•Customer spotting•National census•Demographic Data Vendors•Geographic Information System (GIS)•Market Potential Index (MPI)•Spending Potential Index (SPI)•Measuring competition

Methods of estimating demand

The Analog Approach•The current trade area is determined by using the customer spotting technique•Based on the density of the customer from the store, the primary, secondary and tertiary trade area zones are defined•The characteristics of the current store are matched with the potential new stores’ locations to determine the best site

Methods of estimating demand

Regression Analysis•Primary steps similar to the analogue approach•Select appropriate measures of performance, such as per capita sales or market share•Select a set of variables that may be useful in predicting performance•Solve the regression equation and use it to project performance for future sites

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f(x) = 0.00689003909941829 x + 90.1230794773534R² = 0.891672454564296

Sales

Linear (Sales)

Population (Annual)

Sale

s (An

nual

)

Sales = a+b1x1 +b2x2 + …. + bnxnSales

= a+ bnxn j = 1

n

Methods of estimating demandHuff’s Gravity Model

•Loosely based on Newton’s law of gravity•Built on premise that the probability that a given customer will shop in a particular store or a shopping centre becomes larger as the size of the store or centre grows and the distance or travel time from customers to the store or centre shrinks•Objective is to determine the probability that a customer residing in particular area will shop at a particular store or shopping centre

Pij = Sj +

Tijb

Sj+Tijb

j =

1

n

Sales =

IPij j = 1

n

Methods of estimating demand

The best method•The more information available, the better outcome likely to be•Analog and Huff’s models are best when number of stores with obtainable data is small < 30•Regression approach best when there are multiple variables expected to explain sales•Huff gravity model explicitly considers the attractiveness of competition and customer’s distance or travel time to the store or shopping centre•Since Huff’s gravity model usually does not utilise demographic variables, its important to use it in conjunction with the analog or regression methods

Methods of estimating demand

Future methodology•It will be easier to store data on customer in data warehouses•Advance statistical modeling technique such as CHAID (chi square automatic interaction detection) and Spatial allocation models will become popular•GIS will become more sophisticated and more accessible to users

Thank

you