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AMY ANDERSON University of Southern California SSCI 587: GIS/GPS Field Techniques July 13, 2013

Amy @solutionsthroughresearch.com

BRISTOL FARMS EXPANSION: WY, CO, NM

TABLE OF CONTENTS

1.  BACKGROUND & SUMMARY OF APPROACH ..........................................................................................2 

2.  THE SELECTION PROCESS ...........................................................................................................................2 

3.  REQUIRED DATA OUTLINE ..........................................................................................................................3 

3.1  DATA JUSTIFICATION - PURPOSE ......................................................................................................4 

3.1.1  Reference Data (Items 1 & 6 in Table 1) ............................................................................................4 

3.1.2  Transportation Data (Item 2 in Table 1) .............................................................................................4 

3.1.3  Business Data (Items 3, 4, and 9 in Table 1) ......................................................................................4 

3.1.4  Profile Data (Items 4, 5, and 6 in Table 1) .........................................................................................5 

3.1.5  Parameters for analysis (Items 7 and 8 in Table 1).............................................................................5 

3.2  DATA TIMELINE .....................................................................................................................................6 

3.3  OTHER RESOURCES IMPLIED ..............................................................................................................7 

4.  REFERENCES ...................................................................................................................................................7 

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STEP ONE:

Analyze current Bristol Farms stores

• Determine which current Bristol Farms store format they’d like to use as template for expansion (ie. best performer, average of all stores, a group of good stores, etc.)

• Profile customer database to determine the trade area distance most customers travel to the store.  (4)

• Use that  (3‐mile or 5‐minute driving time) as trade area to be profiled regarding demos, consumer spending habits, competition, transportation access, other retailers nearby, proximity to suppliers, etc. (2, 3, 5, 6)

STEP TWO:

Identify available parcels/lots

• Locate available plots or vacant space that:  

• fit the Bristol Farms format (12,000‐30,000 square feet)  (7, 8)

• are near similar retail stores as determined in step 1  (6)• are w/in ideal proximity to potential farmers or local food suppliers (9)

• fall within a gap in competitor’s trade areas (3, 4)

• are within the determined sweet spot of transportation access (highways, public transportation) as determined in Step 1. (2)

STEP THREE:

Analyze and score trade areas of identified space from Step 2 

• Run profile information from Step 1 for trade areas identified  in Step 2 (2, 3, 5, 6)

• Score each trade area based on its “sameness” to the currently successful model analyzed in Step 1

• Choose top 20 matches as the recommended locations

PROCESS OF SELECTION

1. BACKGROUND & SUMMARY OF APPROACH

Bristol Farms, a specialty supermarket with 13 locations in California, is planning to expand operations to Wyoming, Colorado, and New Mexico. Their owner, Endeavour Capital, has fictionally approached me to help them determine where to optimally locate these new stores.

As an independent contractor / consultant on this project the approach discussed herein relies on my background in GIS and assumes the use of software/hardware that I currently am in possession of including ArcMap 10.1.

Assuming Bristol Farms wishes to keep the same California format as they expand, the general approach to be used is a strategy referred to by some as the lookalike strategy. This will provide a deep understanding of the current store profile in California, both from their best performing store, and the average profile of all 13 of their stores (or a specific grouping as defined by the client).

The lookalike strategy will allow us to understand:

demographics and key indicators of current store customers demographics and key indicators of their custom-defined trade area retail profile and competitive pressures of their custom-defined trade area transportation outlets, main arteries and accessibility to their current grocery stores

Once we have captured all the information regarding their current trade areas and customers we will then look to Wyoming, California, and New Mexico to find areas in those states which score the highest “same as” score as their current stores.

Using a layer of available commercial space (either vacant or undeveloped lot) that is the right size (14,000-30,000 square feet) for a Bristol Farms, lots in Wyoming, Colorado, and New Mexico will be pinpointed if they fall within some ideal general parameters regarding zoning districts and transportation access.

These lots will then be analyzed the same way as their current stores (noting demos, key indicators, other retailers, other grocers) and scored with a “same as” score. Highly scoring “same-as” lots will be further analyzed to narrow into 20 ideal locations.

2. THE SELECTION PROCESS

Figure 1 illustrates three main phases to the process. In parentheses a number is listed if it corresponds with a dataset that needs to be acquired. These datasets are detailed in Table 1 on the next page and justified in more detail on page 4.

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3. REQUIRED DATA OUTLINE

The table below indicates the specific types of data needed for the analysis described up to this point.

TABLE 1: Data Required Potential Source(s) Approx. Cost of Dataset

1. Administrative Boundaries (state, county, zip, census tract) For aggregation and reference. Use most recent available. Will come as .shp files.

Census Free

2. Transportation Access (highways, major roads, public transportation) Use most recent available. Will come as .shp files.

Census State Dept of

Transportation

Free

3. Grocery Store Locations (names, type, size) Use most recent available. Will come as addresses or lat/long, geocode in ArcMap. Excessive

cleaning may be needed with D&B/InfoUSA data to de-dupe and verify classification/business status.

1) Bristol Farms 2) Dunn &

Bradstreet 3) InfoGroup

1) Free 2) From 24 cents to 1.50 per

record depending on level of detail per record.

3) For 9493 leads, costs between $1708 and $2278

4. Bristol Farm Customer Data (location, age, income, etc). Use past 12 month customer data (de-duped) Will come as addresses or lat/long, geocode in ArcMap.

Bristol Farms

Free

5. Consumer Profile (age, population, pop growth, household size, income, buying power,

grocery expenditures, demand - supply leakage) Use 2012 Demos Will be used as attribute data aggregated into trade areas or census

tracts or zips and appropriated accordingly when analyzed.

1) Census 2) Esri Business

Analyst Online 3) Esri Business

Analyst Desktop

1) Free 2) Access 200 requests:

$3K/yr 3) TBD

6. Retail Profile (other types of businesses within 3 mile trade areas) Use Current Basemap with labels turned on and zoomed in to

summarize retailers in trade area. Does Bristol Farms locate themselves near another specific store or type of store? If so look for these in CO, WY, NM.

Basemap should allow for this at a general level.

Free with ArcGIS license

7. Land use / Development (to know residential vs commercial vs industrial) Use most recent available Should come as .shp file or layer

Assessor’s office TBD, assuming free…

8. Available Commercial/Retail Space (by lot size and sq foot of indoor space) Use most recent available - point in time Will come as addresses or lat/long, geocode in ArcMap.

Classifieds or development company

TBD, assuming free with manual compilation

9. Farms / Local Food Suppliers (locations, types of food, owners)

D&B, Info Group and/ or State Ag Depts

.25 per record Free, with manual compilation

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3.1 DATA JUSTIFICATION - PURPOSE 3.1.1 Reference Data (Items 1 & 6 in Table 1) For the analysis a series of reference data will be needed. This data is free and is mainly derived of Census and basemap data which is widely available via public websites and as an Esri licensee.

Administrative boundary data will provide appropriate reference tools in order to customize analysis or aggregate demographics to specific counties or zip codes.

An appropriate basemap will allow the analyst to review the area closest to current Bristol Farm locations. By zooming in, labels should appear identifying large retailers that may also exist in the other states. Commonalities can be recognized that can be used to help pinpoint appropriate retail locations in new markets.

If the basemap does not provide this, business data can be purchased and can be used to obtain the same result. Additional manual cleaning and geocoding of the data will be necessary, thus impacting the timeline.

3.1.2 Transportation Data (Item 2 in Table 1) Transportation data, in the form of major highways, arterial roads and also in the form of public transportation are important in order to determine if current Bristol Farms are located within a common distance of major roads or if public transportation is readily accessible near their stores.

Transportation data is also necessary to determine drive-times should this be needed in the trade area analysis. Esri’s Business Analyst Online should provide this service for us if we purchase it. If we attempt to do this on our own, we would need to capture the speed limits of all the roads in order to determine driving distance. Heidi Guenin and Nathan McNeil’s paper, “Evaluating Grocery Store Siting: A Case Study at SE 122nd and SE Foster” from 2009 walks through how to assign drive times. This was done by adding fields for miles, speed limit, and for calculating the minutes based on miles*60/speed.

3.1.3 Business Data (Items 3, 4, and 9 in Table 1) Highly important to this analysis is business data. At a minimum, locations of grocery stores need to be plotted on the map in order to identify the density of competition. Ideally, we’d capture additional data which provides some sense of the size of the store (in square feet, employees, or revenue). We would also want to capture and classify the type of store (wholesalers, chains, independents, gourmet, specialty, discount, big box, etc) in order to better understand the grocery landscape.

Bristol Farms data should be readily available for this analysis based on retrieving it internally. Competitors, both in California and in the three expansion states would need to be derived separately. It is possible that we could capture this data manually without a third-party cost via online sources such as Manta.com, but the data would need to be manually collected from the websites, cleaned and would likely have much higher rates of error in it, missing or duplicated information.

Instead I recommend purchasing a license to Dunn & Bradstreet or InfoGroup to obtain business info. Initial research found that D&B data may run from $0.24 to $1.50 per record depending on the level of detail you’re looking for (see Figure 2).

InfoGroup provides an online criteria form to build a list and receive a quote. I was able to determine there are 9,493 records for food stores in the three expansion states. This would require a lot of manual work to acquire via free sources, so purchasing would be a better idea to have the best address data possible. InfoGroup’s pricing comes in packages and packages range in level of detail.

To receive the most detail about the grocery stores it would cost about $2,300 through InfoGroup, for the three expansion states. This would include mailing address, SIC code, employee size, sales volume, credit rating score, square footage, and more info which

Figure 2: D&B Pricing

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would be valuable attribute data when reviewing the competitive landscape. The data would still need to be cleaned and reviewed for consistency and accuracy before finalizing, but would considerably cut down on error and time.

These tools could also be used to locate food suppliers, farms, and local farmers where Bristol Farms could source their inventory from. Some lists could be manually created via each state’s Department of Agriculture. Colorado lists several items on their website, including farm fresh directory, a crop calendar, and a link to MarketMaker which is a portal to locate “quality source of food from farm and fisheries.” MarketMaker also is active for Wyoming, but not for New Mexico.

3.1.4 Profile Data (Items 4, 5, and 6 in Table 1) Profile data is incredibly important to a grocer trying to expand operations. The market expanded into needs to be one that can bear the additional supply and would welcome a specialty grocer such as Bristol Farms. To understand what areas of the three expansion states that would best suit a Bristol Farms, we first need to understand who the Bristol Farms customer is. To do this, we would engage in Step One from Figure 1.

By taking Bristol Farm’s customer database we will hopefully receive address information. So at a minimum we would be able to geocode their customer data and see a pattern that could clearly define their main trade areas. Are most of their customers within a 5 mile radius or distributed in a pattern along the major highways? Once determining the trade area we would create a custom .shp file within the majority of their customers lived.

We would then create a consumer profile of that trade area. We can manually do this by downloading census shapefiles and American Factfinder datasets to extract the data we’re looking for, but we could also employ Esri Business Analyst to run reports based on our trade areas.

Esri Business Analyst Online pricing is $3,000 for 200 requests, but does not allow you to do more sophisticated modeling and analysis which you could do with Business Analyst Desktop which works in conjunction with ArcMap. Pricing for the Desktop version was not available at the time this was written.

I believe Esri Business Analyst Desktop is the best source of the data. Census data is free but will require quite a bit of time to develop, and would not provide the wealth of information we’d get from an Esri Business Analyst license: 5-year forecasts in population changes, Tapestry segmentation, consumer spending by industry, household budget expenditures, etc. Their reports include compilation of many sources, forecasting, and are already set up to analyze in ArcMap.

The long litany of reports and data available can be found in the Esri Business Analyst Online: Report Reference Guide.

Additionally using the business data or basemap the profile would incorporate competition and other retail highlights. An example of a trade area overview is shown in Figure 3. This would be run for the CA template location and serve as a basis for determining the parameters that will be used for selection of sites in the three expansion states.

3.1.5 Parameters for analysis (Items 7 and 8 in Table 1) Not being a government employee, one of the more difficult pieces of data I’m looking for is zoning and commercial districts / vacancies in each of the expansion states. Many counties have different zoning codes and regulations. In order to really locate the right space for Bristol Farms, an actual vacant space zoned for grocery retail must be found. Denver I noticed has a special zoning regulation regarding food stores, while others may not. OpenColorado.org provides a wealth of datasets but not necessarily ones that are appropriate for this task. The government entities in each of the expansion states will need to be contacted to retrieve the appropriate zoning / parcel information. Due to these restrictions, the analysis may be limited to certain metro areas with better data available.

Figure 3: Sample of a Summarized Trade Area Profile, not Esri based (PolicyLink, 2007)

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Ideally the zoning information would identify parcels that are vacant commercial, but they may not or they may be out of date. Contacting some local commercial developers may help fill in the gaps and get the most recent listings of available retail space and square footage.

3.2 DATA TIMELINE Week 1:

Determine which current Bristol Farms store(s) to base the lookalike strategy on. Compile list of county assessor offices to contact regarding accurate zoning data. Purchase Esri Business Analyst Desktop Purchase license to InfoGroup leads for business data Import and prepare the base and reference layers for CA, WY, CO, NM

Week 2: Acquire Bristol Farms store data, clean, geocode, and begin review of store analytics and neighborhoods Acquire Bristol Farms customer database, clean data, geocode and determine geographic pattern Contact county assessor offices regarding accurate zoning data Pull competitor list from Info Group (grocery stores) and begin cleaning, de-deduping and classifying

stores based on specialty, gourmet, local, chain, discount, etc. Compile list of commercial developers in expansion states who may have access to vacant space data

Week 3: Create and refine the trade area pattern of Bristol Farm store(s). Mile radius or driving time? Create a template of fields and design of trade area profiles, what data to include and/or summarize Use Business Analyst Desktop to profile current Bristol Farms trade area based on template Continue contact with county assessor offices Continue competitor list cleaning and classifying

Week 4: Plot competitor list from Info Group into CA map. Buffer grocery competitors in CA trade area to see

what the average trade area overlap or gap is. Continue work on trade area profile. Don’t forget to review the retail landscape to document other

retailers in their neighborhoods - commonalities between their current stores. Review trade area profile with client. Get feedback. Continue contact with county assessor offices Contact commercial developers about vacant / available space

Week 5: Tweak trade area profile based on client feedback. STEP ONE COMPLETE! Start getting data from county assessors, review and modify for consistency. Pull food supplier list from Info Group and/or MarketMaker and begin cleaning, de-deduping and

classifying records based on applicability to Bristol Farms Review and clean competitor lists for WY, CO, NM. Geocode and plot. Buffer for gaps. Review trade area profile again and determine key parameters to go to expansion states as assumptions.

o Look for Retailer X, Y, and Z -- is there anything near there available? o Look for areas within x miles of freeway and x feet of bus stop o Look for areas where competition gaps occur based on buffer of x miles (is there a reason there’s

a gap? Low income? Public land?) Week 6:

Continue getting and reviewing data from county assessors & commercial developers Confirm parameters for site selection in expansion states based on the CA trade area profile Geocode the food suppliers Geocode the competitors Search expansion states for areas meeting the criteria as listed above (assuming we have the zoning parcel

layers). STEP TWO COMPLETE! Week 7-10 (or longer):

Any areas that meet the parameters should be profiled based on the trade area assumption used for the CA store(s) (distance or drive-time).

If no areas meet the criteria, back off of specific retailers and competition gaps (in that order).

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Trade area profiles should be scored based on similarity to the CA trade area profile created. Continue getting and reviewing data from county assessors & commercial developers

3.3 OTHER RESOURCES IMPLIED The strategies discussed above assume analysis will be completed by an analyst with access to ArcMap10.1. If that is the case, no additional hardware or software requirements are implied that have not been spelled out in the data acquisition and source sections. If ArcMap10.1 is not currently in use by the analyst, system requirements call for Windows 2003 or more recent operating system, 2.2 Ghz minimum CPU speed, Intel Pentium 4, Intel Core Duo or Xeon processors, 2 GB of RAM minimum, 24-bit color depth, 1024x768 screen resolution at 96 dpi, 500 MB minimum swap space, 2.4 GB disk space, and an awesome graphics card running on the latest available driver. Prior to installing ArcGis for Desktop the following software should be installed: IE 7.0 or higher, .NET framework 3.5 SP1, Python 2.7.x and Python 1.6.x.

4. REFERENCES

[1] “Bristol Farms | Your Extraordinary Food Store.” Bristol Farms, n.d. Web. 12 July 2013. <http://www.bristolfarms.com/>

[2] “Colorado MarketMaker.” Colorado Department of Agriculture, n.d. Web. 13 July 2013 <http://co.marketmaker.uiuc.edu/>

[3] “Department of Agriculture - Markets - Publications.” Colorado Department of Agriculture, n.d. Web. 13 July 2013 < http://www.colorado.gov/cs/Satellite/ag_Markets/CBON/1251624534238>

[4] “Leadbuilder Data Fields.” Dunn and Bradstreet, n.d. Web. 13 July 2013. <http://www.hoovers.com/content/dam/english/dnb-solutions/sales-and-marketing/leadbuilder_data_fields_sheet.pdf>

[5] Esri. (2007) GIS Best Practices: GIS for Retail Business. Accessed via: http://www.esri.com/library/bestpractices/retail-business.pdf

[6] “Esri Business Analyst Online | Pricing.” Esri, n.d. Web. 13 July 2013. <http://www.esri.com/software/bao/pricing>

[7] “Esri Business Analyst Online: Report Reference Guide.” Esri, 2012. Web. 13 July 2013. <http://www.esri.com/~/media/Files/Pdfs/library/brochures/pdfs/bao-ref-guide.pdf>

[8] Guenin, Heidi and McNeil, Nathan. (2009) Evaluating Grocery Store Siting: A Case Study at SE 122nd and SE Foster. Accessed via: http://nathanmcneil.files.wordpress.com/2010/05/grocerystoresiting-final.pdf

[9] The Kilduff Company. (2005) Northeast Oklahoma City Grocery Store Location Analysis. http://www.okc.gov/planning/supermarket/supermarket_study.pdf

[10] PolicyLink. (2007) Grocery Store Attraction Strategies. Accessed via: http://www.policylink.org/atf/cf/%7B97C6D565-BB43-406D-A6D5-ECA3BBF35AF0%7D/groceryattraction_final.pdf

[11] Pryll, Jaclyn. (2008) Suitable Locations for Grocery Stores in Underserved Areas, Rochester, NY. Accessed via: http://soa.utexas.edu/files/gis/SupermarketSuitabilityRochester.pdf