Corner Bakery

STI: PopStats™ Helps Corner Bakery Open 3 Dining Concepts

Corner Bakery

STI: PopStats™ Helps Corner Bakery Open 3 Dining Concepts

Holland Burton started using STI: PopStats in her role as VP of Real Estate at Corner Bakery in 2015. But nearly five years later, she’s still finding new variables she didn’t know existed in the data product. For example, one of the datasets she recently discovered in PopStats was STI: LandScape’s 15 neighborhood segmentation categories.

“I found the data by accident when I was looking for other variables. When I dove into the LandScape categories, I realized that these were variables we could definitely use for our affiliate company restaurants, Il Fornaio, especially as it relates to their new small-plate concept stores Osteria del Fornaio,” explains Holland, who handles site selection and analysis for both Corner Bakery and Il Fornaio, which is affiliated with Corner Bakery through its parent company Roark Capital.

The restaurant company currently operates 18 Il Fornaio Italian and 2 Canaletto Ristorante restaurants in California, Nevada, and Colorado. Il Fornaio has been looking for new locations for new Osteria del Fornaio restaurants, as well as for the signature Il Fornaio Trattoria brand. The Osteria del Fornaio concept is a smaller footprint than the Trattoria brand. It will offer small plates, with a focus on handmade pizza and pasta, as well as a significant attention on craft cocktails.

Holland also continues to look for new locations for Corner Bakery Café, which is a fast-casual bakery café concept offering kitchen-crafted options for breakfast, lunch, and dinner, as well as fresh bakery options available throughout the day. In her role as VP of Real Estate, Holland conducts the research needed to find ideal locations for these three wide-ranging concepts — with over 200 stores from coast to coast.

Landing on LandScape

With over 2,000 variables in the PopStats dataset, Holland says she often finds herself searching through the files just to see what new information she can use to help support her site selection recommendations for three vastly different dining concepts.

“If I can enhance my location research presentations with additional data points for our executive team meetings, so much the better. I will feel more confident in the sites being presented, the executive team will have a stronger understanding of why I’m recommending specific locations, and ultimately that will improve their approval rate of new recommended locations,” she explained.

The company has already negotiated its first real estate lease for the new Osteria del Fornaio concept, and has additional locations in the pipeline for the initial rollout. To select each site, the company relied on LandScape data all the way through the site selection process.

“These establishments will be designed to appeal to a younger crowd,” said Holland. “In fact, we’ve already discovered exactly which LandScape categories we need to attract: Thriving Alone and Single in the Suburbs. The consumer characteristics of those two categories, including income, education, and spending habits, correspond perfectly with what we’ll be offering in the Osteria del Fornaio concept. Although this group is considered a target demographic, of course, the concept welcomes potential customers from all demographic categories.”

Claim Your Corner

Prior to assisting the Il Fornaio brands with their site selection criteria, Holland first relied on a wide range of PopStats data to find ideal locations for new Corner Bakery Café locations. Among the most relevant to these sites are current year estimates and household data. But another key variable is transient populations, because the seasonal flow of diners in and out of its trade areas directly impacts the café’s success.

“Understanding the flow of the seasonal populations in trade areas has been somewhat critical in getting our new sites through the corporate approval process,” notes Holland. “In one case, we had chosen a location with a suburban-urban feel, but that also had hotels. However, because it had a lot of permanent housing, upper-level management didn’t think it had enough seasonal traffic.

“Thanks to PopStats transient data (which is provided in the Current Year Estimates Quarterly Historicals and Statistics report option), we were able to provide exact numbers on the flow of seasonal traffic quarter by quarter every year. Being able to show the actual versus perceived population counts put the seasonal ebbs and flows into perspective for our decision makers. As a result, we felt very confident that the area had a solid residential base, along with a good transient population coming into the area on a daily basis throughout the year.

“Having researched this information in advance, I had an answer at a moment’s notice as it related to the transient versus permanent population in the trade area. As a result, we were able to get approval to finalize that lease.”

Another unique aspect of the Corner Bakery Cafe concept is that the restaurants offer catering. As a result, another dataset within PopStats that has become valuable for the company is STI: WorkPlace. This data provides key insight into specific trade areas that can directly support the catering aspect of the operation, such as local employment, white- versus blue-collar jobs, the percent of people in the labor force, and the percent of people unemployed.

Gold Standard in Demographic Data

PopStats data also feeds Corner Bakery Café’s analog spreadsheet, which allows for easy comparisons of the demographic characteristics of new sites to all existing cafes that are open and operating. The company uses this as the backbone of its research for five to ten new store locations every year, as well as for understanding renewals and for insights into the growing third-party delivery business.

“This is critical to our real estate research operation because we need to know that the data we input is reliable,” explained Holland. “We are very picky with our locations and like to operate on the side of caution, but also be ahead of the curve. So, feeling confident in the data plays well in our approach to growth. Data is not always an exact science, but PopStats comes as close to exact as any market researcher is going to find.”

Holland said she’s grown even more confident with PopStats data after attending the PopStats Research Conference in April 2019. “I knew that the dataset was different than other demographic data products, but now I understand why thanks to the PopStats’ team’s explanation of the methodology behind it.

“Until I heard Robert’s talk on the methodology, I had not realized all of the processes that go into creating and verifying the dataset. It’s a strong methodology. Now I know why my peers in the industry consider PopStats the Gold Standard in demographic data. Knowing more about the methodology has made me feel even more confident when I go into meetings with our executive team and recommend new restaurant locations.”

While having confidence in the data supporting her store location recommendations has always been important, it’s even more critical now that “we are so far out from the 2010 U.S. Census,” notes Holland. “Typically, the data gets weaker the further out we are. But not PopStats. It’s staying strong and dependable to the very end.”

Kroger

Kroger Grocery Stores Discover High-Growth Markets with STI: PopStats™ Data

Kroger

Kroger Grocery Stores Discover High-Growth Markets with PopStats™ data

It takes nerves of steel to open a new retail store in a sparsely populated area: Either that or really good population data.

The Kroger Company believes that it has the best data available in STI: PopStats™. “We have complete confidence in PopStats. Its numbers are second to none,” says John LeTourneux, Director of the Corporate Development Research Department. “PopStats provides the demographic foundation of all of our market research.”

Dale Caldwell agrees. “I consider PopStats the Bible of demographic data because of its accuracy and scope,” says the AVP of Kroger’s Research Department, based in Portland, Oregon. “PopStats’ population estimates and projections are essential in all of our market research.”

Kroger performs a wide range of market research, based both on external and internal data, including quarterly updates of PopStats. “We are rigorous in our research, and have developed an extensive database from our 2,500 grocery stores,” says LeTourneux. The Kroger Company operates grocery stores in 31 states under nearly two dozen banners.

Counting on High Growth in New Markets

Kroger uses PopStats in several ways, including two primary market analyses and six specialty research projects. Its primary market research includes adding PopStats population counts and household profiles into gravity models to project sales for new and remodeled grocery stores.

Kroger makes new location decisions based on these models — including into neighborhoods just starting to grow.

“It’s exciting to open a store in a new area and watch the population grow up around it over the first year or two,” notes John. He says that many of Kroger’s 50 stores in the Las Vegas area followed this pattern during that market’s boom years.

“The grocery industry is a very competitive business,” he adds. “To win market share and not play second fiddle, you have to be the first one in a market. PopStats’ accurate population counts are critical to helping us try to be are the first one in fast-growing markets.”

Conducting Specialty Market Research

In addition to its market growth projection models, Kroger also uses PopStats in six specialty research areas:

  1. Metro ethnic distribution reports. Kroger’s research team creates thematic maps of targeted trade areas, which are used for site selection of new stores and to determine if specialty stores should be created to cater to ethnic populations.
  2. Regional ethnic reports. These reports are used to help Kroger ensure that it is meeting EEOC guidelines for employing an ethnically diverse workforce.
  3. Market share analysis for acquisitions. Using population data and per capita weekly expenditure data, these studies measure what affect closing one store will have on other stores in terms of shifting market share.
  4. Market share analysis for advertising. This research helps individual Kroger stores target their advertising dollars to, for example, advertise more heavily to customers it would like to draw or not advertise where it is likely to yield low results.
  5. Demographic reports. Store managers often request these reports to better understand the populations living in their trade areas.
  6. Ethnic trend tracking reports. This is a research project that Kroger will add in the near-future thanks to PopStats addition of five-year projections for ethnicity in its April 2009 quarterly release. “We want to project ethnic population trends so that we can, for example, either build specialty stores in the right neighborhoods or change our product mix in existing stores to be responsive to demographic changes,” explains LeTourneux.

Today, along with its many specialty research projects, Kroger’s market research department continues to look for the next high-growth areas — so they can, once again, “be the first one there and garner the number one position,” says LeTourneux.

To more accurately project population growth in new markets as Kroger does, contact Synergos Technologies today about the STI: PopStats™ data suite today.

Contact us to learn how

Simon Property Group

Simon Makes Multi-Million-Dollar Decisions with PopStats

Simon Property Group

Simon Makes Multi-Million-Dollar Decisions with PopStats

U.S. headlines have been trumpeting the demise of malls for the past several years. And, yet, many malls have been thriving — especially those owned and operated by Simon Property Group. The commercial real estate company has not only purchased existing malls, but also built 10 outlet malls and 2 mixed-use regional malls from 2009 to 2019.

At the center of such successful, multi-million dollar real estate decisions is STI: PopStats, a vital resource of essential data that Simon leaders have used to develop core strategies and facilitate future growth.

As of March 31, 2019, Simon owned or held an interest in 206 income-producing properties, including 107 malls, 69 premium outlets, 14 mills, 4 lifestyle centers, and 12 other retail properties in 37 states and Puerto Rico. These holdings make the firm the largest retail real estate investment trust and the largest U.S. shopping mall operator with total assets over $30 billion.

As a fundamental component of all real estate decisions, PopStats delivers the demographic data that is crucial for Simon’s Real Estate Research team to gain insight on each potential opportunity. These insights are then used to support the executive-level decision-making process.

“When your inventory is as extensive as ours and you’re making multimillion-dollar investments, the demographics of your properties become critical,” stated Clay Hallman, Vice President of Research. “Thankfully, we have great trust in the data we receive from PopStats.”

Analytics for Informed Decisions

Even with its massive success and position as the number one mall operator in the U.S., Simon is constantly working to improve its centers — from comprehensive upgrades to new marketing plans, Simon expands revenue through continual investment in its assets. Every department in the organization uses statistical insights from PopStats data to inform critical business decisions.

Key variables, such as population density, average household income, and educational attainment, are used to better understand the type of residents in close proximity (within miles or drive times) and throughout trade areas. Comparing demographic similarities and differences across the various Simon platforms (Regional Malls, The Mills, & Premium Outlets) provides clarity for those making difficult decisions and meet departmental goals.

Demographic analysis using PopStats data informs Simon leadership in leasing, marketing, acquisition and disposition, and development initiatives. Deciding which retailers to target, where and when to build new outlet malls, and how redevelopments should be executed all rely heavily on having a strong understanding of the market and the associated demographics.

“There’s not a lot of opportunity for new growth right now, mostly because it’s challenging to find the ideal set of variables for a shopping center to succeed,” noted Clay. “Most of the ideal spots have already been discovered, as we learned from our analysis. Finding the right tenant mix, anchor replacement, and opportunities for mixed-use in our existing centers has become more of a priority today. We use PopStats data to support these efforts.”

Data Informs Retailer Partnerships

Demographics are also a factor in helping the company decide which retailers are the best fit for each of Simon’s shopping destinations. Simon partners with retailers that are the perfect match for each site based on trade area and market demographics, while incorporating industry knowledge that comes from being the most prominent mall operator in the country.

“We don’t just target everyone. We aim at the higher-end retailers for our high-end centers, fashion forward brand names for our outlet centers, and retailers geared towards families for our centers that have a large number of children in their trade areas,” said Clay.

“To make our relationships successful with prospective tenants, we can look at factors as simple as comparing the population and incomes across multiple existing locations,” explained Clay. “Typically, we’re looking for potential opportunities in new markets that mimic the demographics of the retailer’s most successful locations throughout the Simon portfolio.

“Finding retailers for our malls requires having the right fit, and each location is a little different. Our PopStats data helps us find that perfect match for each site.”

Achieving Optimal Success

In its 2018 annual report, which marked Simon’s 50th anniversary, the Chairman, CEO, and President, David Simon, acknowledged the challenges in the industry along with the company’s successes. “Over the last 25 years, like many companies and industries, we have dealt with seismic shifts within our industry. In our case, these changes have forced us to be better operators, more thoughtful and astute capital allocators, and willing to invest in our business with conviction, despite the ever-changing environment.”

In his address, he called out some of the most meaningful geo-demographic shifts over the past 25 years, including the changing demographics and psychographics of the consumers — from Baby Boomers to Millennials, and the fluctuating desires for both high-end and value-driven shopping options.

Among the major disruptions and declarations of a supposedly “dead” industry, Simon has become more profitable by being laser-focused on its core strategy — which has provided a foundation to adapt quickly to both economic cycles and the changing role of shopping destinations in consumers’ lives.

Through it all, PopStats has played an integral role in providing the data necessary to support Simon’s continued success, and it has informed many multi-million dollar decisions throughout the company. “At a time when demographics and strategic insights are more important than ever, Simon will continue to use PopStats data to make important decisions in the future,” Clay concluded.

CVS/Pharmacy

CVS Leverages STI: PopStats™ for Optimum Location Oppotunities

CVS/Pharmacy

CVS Leverages STI: PopStats™ for Optimum Location Oppotunities

CVS/pharmacy is not content simply to know that 10,000 people live in a one-mile geographic area. The company also wants to know exactly how best to position a new store relative to that population and to its competitors.

The national drug store chain gains this clear-cut insight with the help of demographic reports, trade area maps, spatial interaction models, supply-demand analysis, sales forecasting studies, and regression models fueled with STI: PopStats data, its demographic data of choice.

“We’re often looking at two or three sites within a one-mile radius, and we want to zero in on the exact right spot for maximum sales opportunities,” explains Hartwell Hooper, Director of Market Research of the CVS Realty Company. “By applying variables from PopStats, like income, age, and ethnicity, to our analysis, we can do that, even at lower geographic levels — and with extreme confidence.”

In fact, confidence in PopStats data was the deciding factor in CVS’s switch from another data product in 2004. “We conducted side-by-side comparisons of PopStats block-group data with aerial views of our markets and saw that PopStats was doing a much better job of capturing population growth,” says Todd Galusha, Senior Market Research Analyst. “The data from our previous vendor frequently did not match field reports or aerial views, particularly in high-growth areas.”

Expanding Business Possibilities

CVS currently operates almost 7,000 CVS/pharmacy and Longs Drugs stores in 45 states. Despite national economic conditions in 2008 and 2009, CVS has continued to expand their square footage at an annual rate of two to three percent. This equates to 250 to 300 projects per annum, with about a 50-50 split between new locations and relocations.

“We see the slowing economy as a growth opportunity, because real estate prices are lower,” notes Hartwell. “With our bi-annual delivery of PopStats data, we can literally see which areas are growing and declining as the economy fluctuates.”

CVS is also able to see seasonal changes in specific trade areas using PopStats data, such as Cape Cod and parts of Arizona. “Some trade areas have huge spikes of seasonal population,” notes Hartwell. “With the seasonality data in PopStats, we can identify those changes and make strategic business decisions that support sales growth.”

Along with gaining confidence in its data, CVS also gained greater customer service. “Never before could we go to the source of our data with questions; normally, we were three to four layers removed from the source,” explains Hartwell. “Now we can speak directly with Robert (Welch) to discuss any issues we might have such as how he came to certain population numbers and how to use some of PopStats’ specialty data. Synergos Technologies’ unique level of customer service raises our confidence in the data even more.”

Taking PopStats Beyond Real Estate

In late 2008, CVS’s real estate division launched an interactive online mapping program powered with PopStats data. Today, the real estate division can access demographic maps and reports on demand. Several other departments are actively using the web-based tool to make strategic decisions related to individual stores, such as:

  • Merchandising. Uses the demographic tool to make decisions on stocking different products in different stores.
  • Pricing. Uses the population data to examine the customer mix around individual stores and make strategic pricing decisions.
  • Advertising. Uses the online analytic program in a variety of ways, including determining in-store signage needs and deciding when and where to make targeted promotional offers to specific customer groups.

“We want to bring value to every part of the company, especially in this economy,” says David Hansen, Market Research Manager. “With access to the best data, other departments can also make better decisions.”

“We have been getting excellent feedback on our analytic services,” notes Hartwell. “Other departments appreciate having easy access to accurate and timely demographic information to help boost their strategic business decisions – just as much as we do.”

To more accurately target ideal locations as CVS does, contact Synergos Technologies today about the STI: PopStats™ data suite.

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A Migrating Population

Using IRS Data to Track Movement Patterns

A Migrating Population

Using IRS Data to Track Movement Patterns

Understanding the ebb and flow of where people move across the country is crucial to making critical site location decisions. That is why we utilized the latest available IRS data to determine where and from people are moving. We are also able to determine average household income from aggregate income data to understand where higher incomes are moving. The need for past migration trends is more important now more than ever, and something we have commonly been asked about in regards to the COVID-19 pandemic.

Here’s an example:

Check out the downloads below to view our full library of data visualizations showcasing population migration impacted by COVID-19: 

  • There are 3 sets of downloads. File names are based on FIPS code:
    • Set 1 “OutMigbyState.zip” – includes maps for the 50 states (and DC) and shows the out-migration from the state in question. (51 maps, 48mb) (Download)
    • Set 2 “InMig_County.zip” – has county-level maps visualizing inflow for all counties with at least 100 counties of origin(there are 109 counties that fit that criteria). (108 maps, 72mb) (Download)
    • Set 3 “InMig_OutST_County.zip” shows the same as previous but excludes those counties in the same state. (108 maps, 72mb) (Download)
    • (Download All) (267 maps, 192mb total)
  • Reading the maps:
    • Height represents the number of IRS exemptions with a 99.5 percentile cut off to remove outliers.
    • Color represents income with a limit of $200,000 annual household income. Red represents the destination county.

STI: PopStats™ April & July 2020 COVID-19 Related Impacts

Different data points on how COVID-19 has affected the United States

STI: PopStats™ April & July 2020 COVID-19 Related Impacts

Different data points on how COVID-19 has affected the United States

The COVID-19 Pandemic has had a large effect on the daily lives of Americans, as well as causing substantial disruption to the US economy. Many of our clients, especially those across the retail, grocery, and real-estate investment industries are attempting to quantify those effects on their operations. We hope the following maps help illustrate the demographic and economic factors and their impact on the April & July 2020 PopStats Estimates, July and October Releases. As we discuss these estimates it is important to remember that our estimates are point in time, and the estimates for April and July are April 1st and July 1st estimates, respectively.

Most Immediate Impacts – Economic

–  Unemployment increased nationally by about 1% in April and 7% by July. The following are the Unemployment rates as of the 1st of January, April, and July mapped at a county level.
Unemployment Rate by County as of January 1st 2020, 20% limit
Unemployment Rate by County as of April 1st 2020, 20% limit
- Unemployment Rate by County as of July 1st 2020, 20% limit
  • GDP started to dip in April but was more clearly evident with a ~10% national drop in July.
Percentage Change in GDP by County from April 1st 2020 to July 1st 2020, limits of -15% to 15%
Percentage Change in GDP by County from January 1st 2020 to July 1st 2020, limits of -15% to 15
  • Economic Vitality – Economic Vitality is a custom Synergos Technologies, Inc. variable set included in STI: PopStats™. It measures the association between the number of workers in individual industries and our own proprietary stock market indices. This comes in two versions – indexed and non-indexed (both with history). The non-indexed version shows a more historic picture of stock market changes for the relevant industry mix in local areas. While the indexed version shows the relative performance of the local area versus the nation. This was one of the first indicators that we directed our clients to review with the April estimate. Given the frequent and up-to-date nature of the stock source data, it immediately displayed the stock market changes that were occurring in early April. However, there is no longer the depth of decline that was seen in April because as of July 1st the stock market had started to rebound. A possible issue here is that the stock market rebound may not be equally correlated with consumer confidence (one of the main goals of this measure). It may be helpful to adjust these measures by an estimated overvalue, or an estimate of inflated value if you have been historically using the non-indexed Economic Vitality measures. The indexed version should still show the relative performance of local industry mix.
Economic Vitality (non-indexed) by County from January 1st 2020, limits of 50 to 250
Economic Vitality (non-indexed) by County from April 1st 2020, limits of 50 to 250
Economic Vitality (non-indexed) by County from July 1st 2020, limits of 50 to 250
  • Unaffected field sets: rent, home values, income, enrollment, and labor force. These field sets rely on source data that lags the current period. While they may be affected by current conditions, to what degree cannot be currently determined nor accurately quantified as of this October 2020 release.

Vacation / Transient Population – One of the hardest hit sectors has been hospitality with hotel occupancy plummeting. Transient Population data in PopStats is based upon hotel, RV, and campground estimated occupancy. We did not adjust April, but with this July estimate we felt the data dictated making a few adjustments. We determined state-level adjustments to be made through researching hotel occupancy rates. While this lacks the geographic granularity we typically require, it helps to differentiate the relatively low impacts in a few areas versus the extreme effects, such as in Hawaii.

Here is a Map of July 2019 to July 2020 percentage change in our estimate of transient population. Grey represents NA values that occur from 0 Transient Pop.

Transient Pop Percentage Change by County from July 1st 2019 to July 1st 2020, limits of 0%,-80%
  • Seasonal Population – No adjustments have been made to seasonal population currently as any change here will take a while to show up in source data. Still, this may be a very good field set to review. People with seasonal homes may have taken up residence in these areas earlier or for longer amounts of time (we’ll touch more on that topic later). An important note about seasonal population is that it is specific to a quarter of occupancy. Therefore, if you want to know the total annual seasonal pop, you would need to total the last 4 quarters. This can be easily done since this field has 8 quarters of history.
  • The following maps illustrate the Seasonal Population by County for July 2020, April 2020, Jan 2020, and Oct 2019:
Seasonal Pop per 100 Population by County from July 1st 2020, limits of 0,-15
Seasonal Pop per 100 Population by County from April 1st 2020, limits of 0,-15
Seasonal Pop per 100 Population by County from January 1st 2020, limits of 0,-15
Seasonal Pop per 100 Population by County from October 1st 2019, limits of 0,-15

Current Population Change

  • Population Methodology – Our models for population pick up both decline and growth very accurately. This is due to the use of postal data and delivery statistics in our models. We’ll see the change in our estimates as housing units are built and become occupied or vacant.
Population Percentage Change by County from July 1st 2019 to July 1st 2020, limits of -2%,2%
  • New York and Seasonal housing shift. One of the most publicized areas of out-migration and the resulting population shift has been New York City. It has also been one of the areas our customers have most asked about.
Net Migration per 100 Pop for New York City by BG from July 1st 2019 to July 1st 2020, limits 1, -1

Net Migration here is determined by looking at population changes year-over-year and removing birth and death components. While this is a high level of out-migration, New York City has also regularly been experiencing out-migration. This is not as much of an exodus as indicated in many publications. That does not mean that there hasn’t been a large exodus from the area. This exodus has not resulted in, as of yet (July 1st), the equivalent decrease in housing ocupancy. That may sound counter intuitive, and for most parts of the country it would be, but there is a unique situation with a sizeable portion of this most recent out-migration event in New York being  in large part due to people leaving for their seasonal homes.

 

In PopStats, seasonal homes are determined via data from the Census Bureau, and are defined as residences occupied for less than 6 months a year. This is similar to how the IRS, most states and localities determine tax liabilities. We then estimate when those seasonal homes are likely occupied. Concerning the people who left New York, there is a strong chance that they did not sell their homes there or end their leases. Meaning that they are still receiving mail at these addresses.  Should they choose to not return and remain in their seasonal residence for more than 6 months, eventually the proportion of seasonal homes in New York will increase and those elsewhere decrease. At this point that result is uncertain. Some people will choose to return to the city. Some will not.  

 

A similar situation to watch are those that have purchased homes elsewhere (or moved seasonally) that are in the process of selling their residences. It is not overly common for a large amout of people to purchase a house and vacate their current residence before selling for an extended period of time. Likewise, those that have abandoned leases will remain as residents of those leases until they complete the move-out process. These situations will be captured further in our estimates over the next several quarters. Ultimately, many of those that have fled the city will still be counted as current residents. We will montior future quarters to see how this changes over time.

Seasonal Pop per 100 Pop New York City by BG from July 1st 2020, limits of 0,-15

Migration – Origin Destination

  • Related to New York, and more generally out-migration across the US, we have been asked about the destination of those moves. Unfortunately, there is not an accurate, current source that we can recommend here. We are able to recommend a slightly older source. The IRS publishes county level data on origin/destination migration data. We include this data in our LandScape product, and it’s estimated to the block group level for the top 50 counties. We have also previously sold a processed version of this dataset to interested customers.
  • 3D Migration Map – IRS 2017 to 2018 Exemptions – Height represent number from the State of New York to each county (limit of 99.5 percentile), Color depicts percentage of that counties inflow from the State of New York (limit of 20%).  The higher the bar the more people who moved from NY. The more blue the bar the greater proportion that New Yorkers make up of incoming migration.

In conclusion – There exists no data source with geographic granularity that allows us to say these moves or changes are all attached to Covid 19.  We have a “sense” that people are moving out of New York and that early and extended seasonal migration stays might turn into permanent out migration.  However, this is not a hard fact as of yet.  The reasoning’s here could also be multifaceted. It could be COVID related, taxes related, or a combination of these and other reasons.  The ability for many more people to work from home, has no doubt allowed for changes of residency – but are these permanent?  It’s too early to tell, at least quantifiably.  The estimates over time will continue to morph as more data becomes available.  We will continue to publish field comparisons, allowing our customers to better understand demographic changes across the country over time.

Chipotle Mexican Grill

STI: PopStats™ Fuels Chipotle’s Healthy Growth

Chipotle Mexican Grill

STI: PopStats™ Fuels Chipotle’s Healthy Growth

With its unique restaurant philosophy focused on healthy fast food, Chipotle Mexican Grill is known in the marketplace as one of the most innovative and progressive Quick Services Restaurants today. What’s not well known by the average consumer is how savvy Chipotle is about growing its business.

As of June 2014, Chipotle had 1,681 restaurant locations and a plan to grow its restaurant count by almost 200 new locations that year and 200 more in 2015. What’s more, planning the opening of two new store concepts with distinct menus to attract new communities of diners. These included the ShopHouse Southeast Asian Kitchen and Pizzeria Locale.

One community that is well aware of Chipotle’s healthy growth trajectory is the investment community. In mid-2014, The Motley Fool investment website reported:

  • “The latest earnings results from Chipotle Mexican Grill confirm that the fast-casual restaurant company is the top growth story in the industry …
  • “The most impressive aspect of Chipotle’s growth story is perhaps that it shows no signs of stopping any time soon, even though the company already has a rather large domestic presence. The larger and more important part of the Chipotle growth story is twofold: international expansion and growth via new brands.”

Chipotle’s Secret Weapon for Rapid U.S. Growth is PopStats

While the investors are well aware of Chipotle’s high-growth trajectory, what they may not know is that one of Chipotle’s secret weapons for choosing the best U.S. locations for all of its stores is STI: PopStats.

However, Ross Wootton, Chipotle’s Manager of Real Estate Strategy & Research, definitely credits PopStats data — along with the QSR’s unique approach to finding new locations for the new concepts, which includes even scouting locations at food courts, airports, and military bases.

The first step in Wootton’s market research is to find every possible location across the country for each restaurant concept. He accomplishes this by scanning the country using two hexagonal grid models to gain both long- and short-range views of location opportunities based on home populations, daytime populations, and trade area sizes.

Ross calls the scans the “20/20” and the “10/10.” The 20/20 scan includes home populations over 20,000, daytime populations over 20,000, and two-mile trade areas. Similarly, the 10/10 scan includes home populations over 10,000, daytime populations over 10,000, and one-mile trade areas.

“This scan netted 654 trade areas that matched the criteria: 244 in the west, 185 central, and 225 in the northeast,” Wootton said. “I presented the results to the company’s management team to help them determine the next best locations for the new store concepts. With that insight, they could select the markets they wanted to investigate further from the list.”

PopStats Data Fuels QSR’s Growth at Every Stage

Chipotle’s growth trajectory shows no signs of slowing down. Standing at almost 2,000 locations, the QSR is planning to hit 3,000 next. What’s more, the co-CEO Steve Ells stated in the press that Chipotle’s potential for growth is “4,000 units and likely greater.”

All of the new stores will not necessarily be the same size as its current restaurants. Chipotle is experimenting with smaller store footprints with limited seating. It is looking for those smaller opportunities now with the help of PopStats.

“Because PopStats provides demographic data at the block group level, it helps us zero in tightly on ideal locations for our new smaller storefronts,” said Wootton. “This has turned out to be a great advantage for our new direction.”

For the next stage of Chipotle’s location research, Wootton is using PopStats’ metro area populations and daytime estimates to help map out the chain’s future growth potential.

“Because our brand appeals to residents and workers during the daytime, this data helps us prioritize all of the markets we want to pursue, so that we can hone in on only those markets with the highest unit growth potential.”

Along with location selection, Chipotle also relies on PopStats for sales estimates. Once the company opens new stores in new locations, “We use PopStats on a daily basis to help estimate first-year sales at all of our new U.S. locations,” says Wootton. “This helps us not only track our success, but also build our confidence in our location decisions.”

Wootton said that he is anticipating continued rapid growth of the chain as the healthy food concept continues its rapid growth trajectory. He feels confident on making every new store selection thanks to having his decisions supported by PopStats’ pinpoint precision. “I feel like the data is the secret weapon to my success,” he concluded.

Birchwood Resultants

Birchwood Resultants Beats Chain Average with STI: PopStats™

Birchwood Resultants

Birchwood Resultants Beats Chain Average with STI: PopStats™

In 2015, La Madeleine, the popular Country French café bakery chain, decided to make two significant changes to its business operation, including an updated store design, opening new stores, and expanding into new regions. To achieve these goals, La Madeleine called real estate modeling company Birchwood Resultants to conduct its research.

In 2015, La Madeleine, the popular Country French café bakery chain, decided to make two significant changes to its business operation, including an updated store design, opening new stores, and expanding into new regions. To achieve these goals, La Madeleine called real estate modeling company Birchwood Resultants to conduct its research.

To ensure its research produced the ideal results for La Madeleine, Birchwood Resultants called on STI: PopStats and STI: LandScape datasets. The consumer research and real estate modeling company knew it could depend on this data to deliver the demographic accuracy its customers demand.

“La Madeleine is a very successful, long-running bakery-café chain, predominantly in the Southwest region,” stated Bill McClave, co-owner of Birchwood Resultants, along with co-owner Lissy Bethmann. “With a new remodel program, they wanted to move into new regions beyond their stronghold in the southwest to broaden and deepen their appeal to their target customers.”

STI: PopStats™ and STI: LandScape™ Support La Madeleine’s Expansion and Upgrades

To help the restaurant chain determine which stores to remodel first and where to open new stores, Birchwood Resultants created a new set of real estate analytic models. The company also identified the chain’s brand-critical consumers and created a profile that represented the vast majority of its customers.

With the new models and customer profiles in place, Birchwood Resultants conducted its market analytics in three major steps:

  1. Using Landscape, they evaluated all 210 U.S. DMAs for their alignment with La Madeleine’s targeted brand critical consumer profile.
  2. Then they mapped La Madeleine’s highest priority DMAs for the trade areas that have the highest densities of La Madeleine’s ideal brand-critical customers.
  3. The final phase involved modeling new sites identified in the field to build out the targeted trade areas.

So far, the research has pointed La Madeleine to several ideal new locations and remodels for the restaurant chain. For example, it identified an optimal new location in a Houston, Texas market. “Today that store is beating the chain average,” said Mr. McClave.

Data Accuracy is the Key to Market Research Success

Birchwood Resultants speaks highly about the accuracy of PopStats and LandScape data. Particularly because as a real estate modeling company, it has faced the same problems experienced by every other location-focused company — population data estimates have higher variance the further they get from the decennial U.S. Census. As a result, most population counts become less accurate and less dependable every year until the next Census.

Referring to his experience, Bill said, “It’s easy to have accurate population counts the first year after the Census. But thereafter, traditional estimates deteriorate every year.”

Accuracy is the main reason Birchwood Resultants began using PopStats several years ago and continues to depend on it today. “We’ve tested PopStats against other vendors’ population data and it’s extremely accurate,” noted Bill. “PopStats is a very solid database to use in building real estate models.

The company also gains a significant advantage when using lifestyle segmentation in the real estate models it builds. “Understanding a company’s ideal consumer lifestyle is an absolutely critical step in identifying consumer pockets within trade areas,” noted Lissy. “When you look at correlation, everything pales in comparison to consumer lifestyle segmentation.”

Bill concurs. “Alignment with consumer profiles is a must-have. It gives us a much higher correlation to brand performance than demographic data alone because it groups people based on how they live their lives. The ideal scenario in all of our market research projects is to have both PopStats and lifestyle segmentation powering our research models,” concluded Bill.

Academy Sports + Outdoors

STI: PopStats™ Informs Most Departments at Academy

Academy Sports + Outdoors

STI: PopStats™ Informs Most Departments at Academy

At one point in its long history of providing communities across the country with sports and outdoor equipment, Academy Sports and Outdoors identified a few underperforming stores in its network. Naturally, the retailer began investigating the problem. Critical tools in this research were its three key datasets — STI: PopStats™, STI: LandScape™, and STI: Spending Patterns™.

The research revealed that the problem was not the locations, but the stores’ merchandising strategies. The underperforming stores were not stocked in a locally relevant way to fit their neighborhood demographics. The diagnosis inspired the company to rethink its merchandising strategies and make locally focused changes. As soon as they made changes, sales increased. This scenario is just one example how the power of geodemographic data can solve problems and help companies make business decisions beyond strictly the real estate department. In fact, Academy has been extending its market research services outside of its real estate department for several years — bringing the power of data to several other departments in the company.

STI Data Informs Academy’s Business Decision

Gaining critical insight for site selection is the reason why Academy switched to STI data after using another company’s data for several years. “We’d been hearing about PopStats in our industry. When our contract was coming up for renewal with another vendor, we took the opportunity to evaluate PopStats and found that it was superior,” said Rich Babson, Real Estate Research at Academy. “PopStats was more accurate and more current, which is especially important the further out we get from the decennial U.S. Census. With our previous data product, the further we got from the Census, the bigger the population estimate variances were from reality. But with PopStats we’ve found that the data stays consistent and the error rate stays small. This is important to us because the more accurate the data is, the better informed our decisions are.” Along with PopStats, Academy also uses LandScape neighborhood segmentation data and Spending Patterns consumer spending data. LandScape has helped Academy identify its ideal neighborhood segments. Spending Patterns informs product demand analysis.

Neighborhood-Specific Merchandising

To better understand its consumers, Academy performed an in-depth study to determine its ideal neighborhood lifestyle segments using LandScape. In particular, it wanted to identify consumers who fit its ideal customer personas, including outdoorsmen, military personnel, soccer moms, and fitness buffs. Using LandScape’s 72 neighborhood segments, the company looked at neighborhoods where its best- and lowest-performing stores were located. From there, it identified patterns that shaped its understanding of its ideal neighborhood segments. “One of the main things I like about LandScape is that the segments are the same across the nation versus our former vendor’s product, which was heavily influenced by regional consumer characteristics,” explained Rich. “With the old system, the consumers in the segments in which we do well — in Texas and Oklahoma, for example — were not home to the same consumers who live in Florida and North Carolina. With LandScape, I get consistent neighborhood segments across the country.” Academy now uses its LandScape-based neighborhood segmentation insight in all site selection research. What’s more, the merchandising and marketing departments rely on neighborhood segmentation research, as well. “For sporting goods, it’s critical to know who our customers are beyond the demographic data,” said Rich. “Trade areas with the same demographic characteristics can be inhabited by people with very different lifestyles. Knowing the exact lifestyles of our ideal customers gives us critical consumer insight. It’s much more profitable for our company to identify areas with large pockets of our ideal customers and, similarly, to avoid areas with the wrong types of consumer lifestyles.” Along with PopStats and LandScape, the SpendingPatterns data plays an important role in helping Academy determine each store’s ideal merchandising mix. Before opening a new store, the research team creates a demand analysis to assess what products will fit best with the lifestyles of the consumers living in that area. In this way, the stores minimize some products, such as athletic apparel, and maximize other categories, such as sports team apparel, depending on the SpendingPatterns data. Rich particularly likes that the data is consistent across the country, so they can depend on the insight no matter where in the U.S. they are researching.

Research-Driven Business Decisions

For real estate, the research department uses STI data in a variety of ways including:
  • Creates executive committee presentations for every new store location
  • Conducts property analysis for new locations, including lifestyle segments
  • Conducts existing store analysis to improve performance issues
  • Employs regression analysis to understand which variables impact store performance
  • Creates forecasts using over 300 store-level attributes
Examples of research projects for other departments include these requests:
  • Advertising Department – requested maps of zip codes in trade areas for advertising distribution and distance calculators to brand-name competitors
  • Promotions Department of a Regional Store – requested a map of the shooting schools within a specific proximity to its stores, so the stores could reach out and set up partnerships with them
  • Human Resource Department – requested maps of healthcare facilities located near contracted e-commerce employees to provide them with medical services information to meet labor compliance regulations
  • Merchandise Department – requested analog models to support merchandising decisions for each department within each store
In fact, conducting research for the merchandising department is a major focus of Academy’s trade area research, because there are such big regional differences in its customer bases. For example, some areas are home to hunters or fishermen, while others are team-sport-oriented. “This analysis has proven to deliver a significant impact on our merchandising,” notes Rich. “Every store in which it’s been executed has experienced significant performance improvements. That’s the decision-making power we’ve come to expect from our powerful suite of STI datasets.”

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