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Tools For Identifying & Recruiting Retail

Tools For Identifying & Recruiting Retail . Who Is Buxton?. Largest provider of customer analytics solutions Analyzed every type of retail, restaurant, healthcare and service concept Over 5 billion square feet of analysis in 2007

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Tools For Identifying & Recruiting Retail

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  1. Tools For Identifying & Recruiting Retail

  2. Who Is Buxton? • Largest provider of customer analytics solutions • Analyzed every type of retail, restaurant, healthcare and service concept • Over 5 billion square feet of analysis in 2007 • Over 1,700 clients including retailers, restaurants, developers and communities • Recognized as a Fast Company Fast 50 Company in 2005 • Assisted more than 400 public sector clients develop millions of square feet of retail

  3. Some of Buxton’s Clients

  4. What is CommunityID? • Retailer Matching Matches the specific retail and restaurant concepts to the buying habits and lifestyles of the consumers living in your trade area • Unique Program Is the only program of its kind that can factually identify exactly which concepts should be in your community

  5. Where is CommunityID? CommunityID Engagements 400+ Public Sector clients in 38 States

  6. Buxton Engagements in Ohio • Montgomery County (Joe Tuss – ED Director) • Mentor (Ron Traub – Director of ED) • Kent (Dave Ruller – City Manager) • Miami Township (Dave Duckworth – Township Administrator)

  7. Benefits of a Strong Retail Sector • Enhances residents’ lifestyles with more shopping and dining choices • Increases sales and property taxes • Decreases retail leakage • New, permanent jobs • Expands economic opportunities by attracting more people and businesses

  8. Step 1: Identify The Trade Area

  9. City Limit Trade Area

  10. Ring Trade Area

  11. Retailers Locate Near Customers Customers think in terms of time and convenience… they “think” drive time. 1 Min 3 Min Shortest route is calculated in minutes for each customer 4 Min 2 Min

  12. Drive Time Trade Area

  13. Trade Areas

  14. Step 2: Identify The Customer

  15. Demographic Methodology Age Sex Race Income • Traditionally, locations were selected based on:

  16. Problems with Demographics • Demographic data is too general and too stale • Identifies people not customers • Does not explain what people like to buy • Does not define a true trade area • Not driving most retailers location decisions • May do more harm than good…

  17. Psychographics, not Demographics It’s Customers, not People • Now, customers can be identified based on: Lifestyles Purchase behavior Media habits

  18. Buxton Data 35 terabytes of data on over 120 million households Managed In-House

  19. 250 In-House Data Sources Trade Potential Consumer Data Shopping Centers Business Data Restaurant Data Segmentation Consumer Profiles Demographics Telecommunications Automobile Data Street Data

  20. Segmentation All U.S. households fall into 1 of 66 psychographic segments

  21. Purchase Behavior • Psychographics focuses on • Customer Lifestyles • Media Habits • Purchasing Behavior Segment 29 American Dreams

  22. Census Profile Customer OneCustomer Two Age: 40 Year Old Male 44 Year Old Male Income: $102,000 Income $110,000 Income Ethnicity: Caucasian Caucasian Marital Status: Married Married Kids: 2 Children 3 Children Education: Post-graduate degree College Graduate

  23. Psychographic Profile Customer OneCustomer Two Owns: iPod Power Boat Eats: Boston Market Chili’s Grill & Bar Reads: Barron’s Field & Stream Watches: PGA Tour Country Music TV Drives: BMW 5 Series Dodge Ram Drinks: White Wine Bud Light

  24. Remember: Customers, Not People Total households Customers • Trade Area “A” • Trade Area “B” Total Households: 36,087 Total Households: 96,540 Ben & Jerry’s Customers: 14,443 Ben & Jerry’s Customers: 14,540

  25. Step 3: Match The Customers to Retailers

  26. Retailer Profile Ben & Jerry’s Percent Segment Dominant Segments

  27. Trade Area Profile These segments represent the dominant segments for Ben & Jerry’s Dominant Segments

  28. Trade Area Matches Retailer Dominant Segments

  29. Trade Area Does Not Match Retailer Dominant Segments

  30. Step 4: Tools forSelling The Trade Area

  31. Retail Leakage/Surplus Analysis • How many dollars are leaving • What stores attract outside dollars • How strong is your retail sector • What are our retail opportunities Example of Major Store Type. Buxton analysis includes details within Major Store Types and analysis by Product Type

  32. Sample Tenant Match

  33. Custom Pursuit Packages –Sample Score Sheet Speak the Retailer’s Language

  34. Custom Pursuit Packages –Sample Score Sheet 15,350

  35. CommunityID SCOUT 2.0 Market your community using SCOUT’s dynamic online tools Enter SCOUT together with your target retailer Click to show your site Click to show the trade area Click to show the retailer’s dominant segment households Click Match Report to show the retailer you are their target market

  36. CommunityID SCOUT 2.0 Market your community using SCOUT’s dynamic online tools Click on a Retailer Marketing Package to show all the data relative to the target retailer and your community You can send this and other reports electronically to your prospect

  37. Ongoing Client SupportBuxton @ ICSC Spring Convention

  38. Ongoing Client Support Buxton @ ICSC Spring Convention

  39. Summary • Identify The Trade Area • Identify The Customers • Match The Customers to Retailers • Aggressively Market to Matching Retailers • Get Retailers & Developers Interested • Bring New Retail to Your Community

  40. Sample Projects

  41. Downtown San Jose, CA • One of the most affluent trade areas in America • Many restaurants, NO retail • Daytime Profile overlaid onto Residential profile to see if any retailers fit • Can we build a case for Border’s? Yes! • Benchmarked downtown against Long Beach and San Diego (perceived competitors for retail)

  42. Midtown Alliance – Atlanta, GA • Retail Analysis for Peachtree Street Corridor – The “next Michigan Avenue?” • High growth residential development • Adjacent to Georgia Tech campus – what is the impact of the college student? • Huge increase in daytime population – who are these people?

  43. Downtown San Diego Partnership • Profiled eight distinct neighborhoods – both residents and work place • Psychographic Profiling and Analysis of Petco Park (San Diego Padres) visitors • Padres provided specific data sets for analysis: Season ticket holders, suite ticket holders, single game walk up purchases, internet purchases, etc. • “Game Day Profile” - We can then overlay the Padres customer profile onto the existing trade area profile

  44. Barriers to Downtown Retail • Identifying the customer – who is it? • Parking, Access, Visibility • Assembling viable sites • Unmotivated property owners • Unmotivated brokers • Existing retail outside of downtown

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