1. PPT 8-1 5 th Edition

2. PPT 8-2 McGraw-Hill/Irwin Levy/Weitz: Retailing Management, 5/e Copyright © 2004 by The McGraw-Hill Companies, Inc. All rights reserved. Site Location Chapter 8

3. PPT 8-3 Retailing Strategy Retail Locations Chapter 7 Site Locations Chapter 8 Human Resource Management Chapter 9 Information and Distribution Systems Chapter 10 Customer Relationship Management Chapter 11 Retail Market and Financial Strategy Chapter 5, 6

4. PPT 8-4 Location Chapters Chapter 7 –General Description of the Location Types –Advantages and Disadvantages of Different Location –Appendix – Terms and Condition Involved in Leasing Sites Chapter 8 –Considerations in Selecting Area for Locating Store –Issues in Evaluating Specific Sites

5. PPT 8-5 Three Levels of Analysis

6. PPT 8-6 Trade Area Issues Which Trade Areas Are Most Attractive for Locating 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 Cannibalization and Less Sales per Store

7. PPT 8-7 Factors Affecting Demand for a Region or Trade Area

8. PPT 8-8 Factors Affecting the Attractiveness of a Site How Attractive Is the Site to the Retailer’s Target Market? –Match Between Trade Area Demographics and Retailer’s Target Market –Likelihood of Customers Coming to Location Convenience Other Attractive Retailers At Location Principle of cumulative attraction - a cluster of similar and complementary retailing activities will have greater drawing power.

9. PPT 8-9 Convenience of Going to Site Accessibility Road pattern and condition Natural and artificial barriers Visibility Traffic flow Parking Congestion Ingress/egress

10. PPT 8-10 In High Traffic Areas Near Anchor Center of Shopping Area Near Stores Selling Complementary Merchandise Clustering Specialty Stores Appealing to Teenagers Better locations cost more Location Within a Center

11. PPT 8-11 Map of Dallas’ North Park Center

12. PPT 8-12 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

13. PPT 8-13 Trade Area Primary zone - 60 to 65 percent of its customers Secondary zone - 20 percent of a store’s sales Tertiary zone - customers who occasionally shop at the store or shopping center

14. PPT 8-14 Factors Defining Trade Areas Accessibility Natural & Physical Barriers Type of Shopping Area Type of Store Competition Parasite Stores

15. PPT 8-15 Oblong Trade Area Caused by Major Highways and Natural Boundaries

16. PPT 8-16 Sources of Information Customer Spotting Census Data Geodemographic Information Systems –ACORN Information on Competition –Yellow Pages

17. PPT 8-17 Customer Spotting Purpose: to spot, or locate, the residences of customers 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

18. PPT 8-18 Census Data of the U.S.. Only once in 10 years. Each household in the country is counted to determine the number of persons per household, household relationships, sex, race age and marital status.

19. PPT 8-19 Geodemographic Information Systems Demographic data vendors specialize in repackaging and updating census-type data. Geographic Information System (GIS) is a computer system that enables analysts to visualize information about their customers’ demographics, buying behavior, and other data in a map format. GIS is a spatial database that stores the location and shape of information. Analysts can identify the boundaries of a trade area and isolate target customer groups

20. PPT 8-20 Indices for Assessing Sales Potential Market Potential Index (MPI) –Number of Households Purchasing a Product or Service in a Trade Area Spending Potential Index (SPI) –Average Amount Spent on a Product or Service by a Household in a Trade Area

21. PPT 8-21 Sources for Measuring Competition The Internet - lists current locations and future sites. Yellow Pages Other Sources: Directories published by trade associations, chambers of commerce, Chain Store Guide, International Council of Shopping Centers, Urban Land Institute, local newspaper advertising departments, municipal and county governments, specialized trade magazines, list brokers

22. PPT 8-22 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

23. PPT 8-23 Competitive Analysis for Edward Breiner

24. PPT 8-24 Methods for Estimating Demand Analog Approach Multiple Regression Analysis Huff’s Model

25. PPT 8-25 The Analog Approach 1. Current trade area is determined by using the customer spotting technique. 2. Based on the density of customers from the store, the primary, secondary and tertiary trade area zones are defined. 3. Match the characteristics of our current store with the potential new stores’ locations to determine the best site. 3 Steps:

26. PPT 8-26 Income Distribution of Three-Mile Ring Surrounding Edward Breiner Optical

27. PPT 8-27 Demographic Trends for Three-Mile Ring Surrounding Edward Breiner Optical

28. PPT 8-28 ACORN Neighborhood Lifestyle Clusters for Three-Mile Ring Breiner Optical

29. PPT 8-29 Descriptions of Largest PRIZM Clusters Surrounding Edward Breiner Optical

30. PPT 8-30 Description of Largest PRIZM Clusters Surrounding Edward Breiner Optical

31. PPT 8-31 Description of Largest PRIZM Clusters Surrounding Edward Breiner Optical

32. PPT 8-32 Description of Largest PRIZM Clusters Surrounding Edward Breiner Optical

33. PPT 8-33 Descriptions of Edward Breiner Optical and Four Potential Locations’ Trade Areas

34. PPT 8-34 Multiple Regression Analysis Need to define the retail trade area potential for retail chains with greater than 20 stores. Similar to the analog approach, it uses statistics rather than judgement to predict sales for a new store.

35. PPT 8-35 Multiple Regression Steps Current trade areas are determined by using the customer spotting technique Primary, secondary, and tertiary zones are determined by plotting customers on a map 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.

36. PPT 8-36 Yearly Sales, Population, and Income for 10 Home Improvement Centers

37. PPT 8-37 Regression of Population on Sales

38. PPT 8-38 Illustration of Regression Approach 1. Specify Regression Model – Identify Critical Predictors of Store Sales Sales = B 0 + B 1 x X 1 + B 2 x X 2 X 1 = population in trade area X2 = average household income in trade area 2. Estimate Weights - B 0,B 1, B 2 3. Use Estimated Weights to Forecast sales Sales = -144,146 + 6,937 x X 1 + 10,132 x X 2 Sales = -144,146 + 6,937 x 55,000 + 10,132 x 28,000 = $521,085

39. PPT 8-39 Huff’s Gravity Model Based on the premise that the probability that a given customer will shop in a particular store or shopping center becomes larger as the size of store or center grows and distance or travel time from customer shrinks

40. PPT 8-40 Huff’s Model Formula

41. PPT 8-41 University and Shopping Centers: Gravity Model Illustration

42. PPT 8-42 Huff’s Model: The Solution P ij = 1000  3 2 (1000  3 2 ) + (500  5 2 ) + (100  1 2 ) 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 areas and then sum them.