Dale Honeycutt, Author at Synergos Technologies, Inc.

Average Home Values Since 2007

How has the housing market performed since the 2007 financial crisis?

Average Home Values Since 2007

How has the housing market performed since the 2007 financial crisis?

The US economy has come a long way since the 2007-2008 financial crisis. State and local economies across the country faced their own unique crises dealing with the housing market collapse. We took a look at STI: PopStats™ numbers to see what other economic factors were affected by the collapse and how they’ve changed since then.

The Housing Market

The subprime mortgage crisis of 2007, was a key contributor to the global financial crisis that followed. Property values across the country hit rock bottom. But not everywhere.

We took a look at PopStats data since 2007 and it clearly shows that some areas were hit harder than others. Some states’ housing markets hardly skipped a beat like Texas, North Dakota, Colorado, etc. While others took it much harder than others like West Virginia, Michigan, etc. See for yourself in this graphic:

Here’s another view of the data:

The following videos are visualizing population density (height) and average home value (color) by county. Each video shows a different view of the United States starting with the west, then central, and finally the east. Both average home value and population density have limits. The data is from Q1 of each year.

Some interesting locations to look at are Austin, Texas (Travis County), Southern Florida, and Minneapolis, Minnesota (Hennepin County).

WEST VIEW 2007-2021

CENTRAL VIEW 2007-2021

EAST VIEW 2007-2021

Taking A Closer Look

As we look at the communities under our scope, we’ll refrain from deriving conclusions as to the exact causes for the observed outcomes. Our expertise lies in generating accurate forecasts and estimates, not in providing this type of analysis, so we’ll leave it up to the reader to infer deeper insights.

The first market we’ll focus on is Austin. It has experienced unprecedented growth in almost every category. The next market we’ll showcase is Phoenix, which took a hard hit at the beginning of the recession, but has experienced a strong recovery. Lastly, we’ll look at Charleston, West Virginia, which didn’t move much at all during the entire 14 year period.

The Markets

Our approach to evaluating these three markets will be to explore their population, unemployment, housing, and GDP in 2007, 2012, 2016, and current-day (Q3 2021).

Austin

In 2007, the Austin market’s population was 1,412,264. At the same time, the city’s unemployment rate was 3.49%, the average home value was $202,964, and GDP running at $70,379.

Austin’s population has exploded over the past 14 years. It’s worth noting that unemployment has increased by 36% when compared to 2007, but unemployment increases many times are a sign of mobility and opportunity for job seekers.

Today, the difference for the highlighted fields is as follows:

- Population: +58%
- Unemployment: +36%
- Average Home Value: +169%
- GDP: +5.2%

Phoenix

In 2007, the Phoenix market’s population was 3,830,898. At the same time, the city’s unemployment rate was 3.34%, the average home value was $360,952, and GDP running at $60,043.

An interesting insight to make about the data listed below is that Phoenix’s housing market was 78% more expensive than Austin’s in 2007. Then the Phoenix market appears to correct into 2012 where the two markets then became comparable. Going forward from 2012, both markets behave similarly.

Today, the difference for the highlighted fields is as follows:

- Population: +31%
- Unemployment: +99%
- Average Home Value: +70%
- GDP: -4.33%

Charleston, WV

In 2007, the Charleston market’s population was 224,942. At the same time, the city’s unemployment rate was 4.17%, the average home value was $121,385, and GDP running at $51,503.

What’s most interesting about the Charleston, WV market, and why we chose to highlight it, is Charleston has a population decline. The only one with a population decline of the three markets we’ve highlighted. This market’s GDP still increased since 2007 despite a population decline.

Today, the difference for the highlighted fields is as follows:

- Population: -4.3%
- Unemployment: +30%
- Average Home Value: +25%
- GDP: +7.5%

Conclusion

When we look at the data for 2007, 2012, 2016, and 2021, we see more nuance as to how each market traversed the challenges it faced. Below is a spreadsheet with the variables we measured, listed by year:

Looking back at the past 14 years, we lived through a crisis that shook the foundation of our economy and begged the question as to whether the American dream of home ownership can remain accessible to all. Since then, many socio-political changes have taken place and we’ve seen the country bounce back and achieve record breaking levels of economic growth. For the past two years, we’ve been living through a global pandemic that has challenged every country in the world, and changed the way Americans view their work, and standard of living. The net effect of these massive changes are yet to be fully realized and quantified, but as always, our data will provide a clearer view of the past so we can better project the future.

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Economic Development in Top Growth Markets

GDP per capita in top growth markets is either slowly increasing, or not at all.

Economic Development in Top Growth Markets

GDP per capita in top growth markets is either slowly increasing, or not at all.

As shocking as it may sound, only 2 of the 5 top growth markets in the United States have a higher GDP per capita now than they did in 2007 after adjusting for inflation. Take a look at these 5 markets and how they compare to their states and the nation.

Running the Numbers

We derived this insight by tracking GDP per capita using our GDP and population fields from 2007 to 2021. We then adjusted these numbers for inflation, based on BEA data, to create an accurate view of how these markets are progressing. The graph below shows how each market stacks up against each other, their states, and the nation (y-axis is in thousands):

There are several different ways GDP can be measured. Our GDP estimates are a GDI (Gross Domestic Income). This allows us to create estimates at a local level and is equivalent to GDP on larger levels. The following four incomes are considered: farm income, personal income, business income, and government income (taxes).

Diving Deeper

If you take a look at the spreadsheet above, the last column reveals that only one market (Charleston) has had a substantial amount of GDP per capita growth that also beat the nation. Two markets, Myrtle Beach and Phoenix, exhibited a decline in GDP per capita, and Boise is hardly displaying an increase. Two economic crashes occurring within the last 14 years are likely large contributing factors to these trends.

The inference that can be made is that the populations moving to these markets add a lower amount of per capita output than the starting per capita output level.

The October release for the July 2021 estimates is available now!

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LandScape Segments Fueling Top Growth Markets

Let’s explore the groups responsible for driving economic vitality in the top growth markets in the United States

LandScape Segments Fueling Top Growth Markets

Let’s explore the groups responsible for driving economic vitality in the top growth markets in the United States

Earlier in 2021, we released our “Top Growth Markets” annual report. This report lists the 26 strongest markets in the United States. In those markets, there are segments of the population that are fueling this growth. We dive into the top 10 markets and determine which segments are responsible for their growth.

What are STI: LandScape™ segments?

STI: Landscape™ is a lifestyle segmentation product that allows a marketer to identify their customer profile from 72 predetermined segments and to pinpoint their location across the U.S. All 72 segments are sorted into 15 categories. Lifestyle segments are determined by race, household type, age, income, and many other factors. Knowing customers’ unique lifestyle attitudes has numerous applications including site selection, marketing, merchandising, and so on.

Knowing what type of customer is in a market, and which ones are growing in an area, is a valuable insight into any untapped potential.

Segments Fueling the Top Markets

In the top 10 of the top markets report, there were a few segments that stood out. The first one was the Sitting Pretty segment. This segment appeared 6 times out of the 50 chances it got. The Sitting Pretty segment falls under our Urban Cliff Climbers category which are high-density neighborhoods that are mostly filled with families that work hard for their well-earned living. They’re a strong representation of the “working class.”

The segment that had the second-highest number of appearances is the Sublime Suburbia segment which appeared 5 times. This segment falls under the Married in the Suburbs category which includes 30-something suburbanites enjoying the fruits of the high-quality suburban lifestyles. They earn very good incomes and they mostly consist of married couples with children.

The segment with the third-highest, and our final segment spotlight, is the Legacy Years segment which appeared 4 times. Legacy years falls under the Specialties category in LandScape which are unique segments that don’t quite fit any other category. These neighborhoods generally host people that range in age of older 50s to early 60s.

As you follow along with the list, use this guide to help you better understand what type of neighborhoods are helping these markets grow. You can also click on each segment to get a more detailed definition. Reach out on the chat or here for detailed descriptions of all 72 segments.

The Segments:

Austin, TX – The highest growth market from the 2021 report is Austin! The area referenced in the report comprises Travis, Hays, and Williamson counties.

The segments fueling the Austin growth are ranked as follows:

Boise, ID – coming up second in the fastest-growing markets is Boise! The counties encompassing this market are Ada, Boise, Payette, and Canyon county.

The segments fueling the Boise market are:

Myrtle Beach, SC – still remaining in the top 5 fastest growing markets is the vacation spot, Myrtle Beach. This market includes Horry county.

The segments fueling the Myrtle Beach market are:

Charleston, SC – the second market in South Carolina claiming its spot on this list is Charleston. The counties included in this market are Charleston, Dorchester, and Colleton county.

The segments fueling the Charleston market are:

Phoenix, AZ – In the middle of a desert climate is the growing Phoenix market. The market includes Maricopa county.

The segments fueling the Phoenix market are:

Lee, FL – Southwest Florida is experiencing healthy growth along the coast from tourism and industry. This market is only comprised of Lee county.

The segments fueling the Lee market are:

Orlando, FL – Central Florida claims a second spot for the sunshine state in our fastest top growth markets. The counties included in this market are Orange, Sumter, Lake, Marion, and Hernando county.

The segments fueling the Orlando market are:

Northwest Pinal, AZ – Arizona received rapid growth in its markets this past year. The only county considered in this market is Pinal County.

The segments fueling this market are:

North Dallas/Fort Worth, TX – The DFW metropolitan area is the 4th largest metro area in the United States. Even with that status, the more northern area of the metro is experiencing some of the biggest growth in the country. The counties included in this market are Denton, Collin, Hunt, and Rockwall.

The segments fueling this market are:

South Nashville – The last top growth market to be discussed will be the southern part of Nashville. The county included in this market is Davidson county.

The segments fueling this market are:

Want to know the definition of all the 72 segments?

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4 of the 5 Most Active Grocery Retailers are PopStats Customers

Here’s why.

4 of the 5 Most Active Grocery Retailers are PopStats Customers

Here’s why.

“Click and Carry” (pickup) is fueling e-commerce for grocery retailers across the nation. This new trend isn’t showing any sign of slowing down, but the fight for the perfect store location is still being fought.

BuildCentral recently released an article listing 2021’s Top 5 Most Active Grocery Retailers in America. It dives into the topic that regardless of the digital age, grocery stores are still ramping up construction of their brick and mortar stores.

Out of the 5 grocers listed in the article, 4 trust STI: PopStats™ to power their market strategy and site-location decisions. These top grocers use PopStats because it is the most up-to-date and accurate geospatial dataset on the market.

This article will dive into the different reasons why they choose PopStats and other Synergos datasets again and again.

Want a free sample of PopStats? Contact us today!

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“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.”

“…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.”

Here at Synergos Technologies, we work under a policy we call, “ACT.”

A – Accuracy
C – Comprehensive
T – Timely

Everything we create and do must fall under these three pillars. They help us to create quality products and services that maintain our status as industry leaders. Let’s dive into how our full data suite falls into these pillars.

Accuracy

Many PopStats customers use our datasets due to their accuracy and dependability. Those attributes come from proven methodologies that allow you to make confident decisions.

There are many different ways are able to check data quality and ensure accuracy in every release. One way is through a “Q&A” process. This is a robust process that involves testing the final product with proprietary procedures before we release the product. We are also constantly creating maps and graphs to see if we can catch any data discrepancies (we like to post our most interesting discoveries online).

Another way we prove the effectiveness of our methodologies is by comparing our estimates to Census and ACS numbers. Our Accuracy whitepaper shows the numbers and how close our population estimates were to the 2010 census. PopStats counted 99.998% of the United States population. Fast forward 10 years to the 2020 census and PopStats counts 99.993% of the population. That’s 20+ years of exceptional accuracy that our competitors aren’t able to achieve.

Out of anyone else in the industry and our competitors. Our estimates were the closest to the Census results. We were even closer than the Census’s own preliminary estimate.

Comprehensive

Comprehensive to us means that we have so many unique, accurate, and updated variables, that you will be able to extensively understand your site-selection research. A few unique variables we create are religion, discretionary income, and economic variables like GDP and mortgage risk. PopStats has the largest selection of fields in a single demographic product (over a thousand), and we update it quarterly.

Moving along, every variable in our datasets is backed by trusted and official sources. Most use more than one source! Some sources that our datasets use are:

You can contact us if you’re interested in learning about our full list of data sources.

We then use proprietary mathematic models to shape the data into estimates. All of these steps create robust datasets that can be used to effectively make decisions beyond site location like what items to stock on the shelves or what kind of advertising would be effective in an area. The opportunities are endless.

Timely

Uniquely, in the realm of demographic estimates, PopStats is the first and only dataset to be released quarterly. No other data provider can duplicate that process a the level of accuracy we do it at. The struggle with that is on-time releases. Synergos Technologies is proud to say that of our 25+ years in business we have never been late on a PopStats delivery. We understand our customers are working diligently to find the best sites for their new store locations. That’s why we also work diligently to make sure they have the tools they require when they need them.

Another factor in our reliability is our industry-leading customer service. Being able to pick up the phone and talk to a person immediately is a thing of the past for most businesses. Not with us. We always have someone at the phone ready to answer questions immediately during business hours. Additionally, we have created multiple points of access to our customer service like email and our new website chatbox. Our excellent system allows us to be proud to say that all customer inquiries are answered within a day of contact, and often within the hour.

Interested in learning more? Contact us today!

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– Extra Material –

The Most Livable Counties – A Discretionary Income Analysis

Consumer spending habits and discretionary income determine the quality of life for many Americans. Which counties are experiencing the best?

The Most Livable Counties – A Discretionary Income Analysis

Consumer spending habits and discretionary income determine the quality of life for many Americans. Which counties are experiencing the best?

America is beginning to return to a more normal state of living. Now that the COVID-19 pandemic is seemingly coming to an end, consumer spending is beginning to increase again. We used STI: PopStats™ data to analyze average household incomes and discretionary incomes to determine where the most livable cities/areas across the country are, and to see where spending is likely to increase the most.

The ranking for the following cities/areas was determined by comparing average discretionary income versus the average household income in a county. The counties with the most discretionary income to spend on goods not considered necessities are ranked higher. With consumer spending ramping back up in America, the areas with more discretionary income will be spending more than others.

Along with our rankings, we included economic indicators unique to the PopStats product like ‘Gross Domestic Product’ and ‘Mortgage Risk.’ These unique variables give further insight into our clients’ potential customers and their custom customer profiles. Mortgage risk is an interesting variable in that it rates an area on its chances of defaulting on a mortgage from 1 to 5, 5 being most likely and 1 being least likely.

All numbers and figures used in this analysis are sourced from STI: PopStats™. Contact Us to learn more about the 1000’s of variables we update quarterly.

Most Livable Counties in the United States

10. Nassau County – Long Island Area

Population: 1,356,138
Average HH Income: $157,016
Average Discretionary Income: $65,977

GDP per Capita: $111,661
Mortgage Risk: 3.2672
Average Disposable Income: $107,841

This county is the first county outside of New York City. A theme that you are going to notice through the rest of this analysis is that “most livable cities” are actually areas right outside of thriving metropolitans. These professionals are benefitting from high salaries and then escaping back to more affordable real estate. This combo allows for more discretionary income worth the extra time spent in the car.

9. Philadelphia – Chester County

Population: 533,178
Average HH Income: $139,215
Average Discretionary Income: $66,893

GDP per Capita: $91,027
Mortgage Risk: 2.7338
Average Disposable Income: $99,520

With a population of over 500,000, Chester county hosts several cities that are reaping the benefits of having a manageable drive time to Philadelphia.

8. The Bay Area

Population: 3,816,251
Average HH Income: $177,761
Average Discretionary Income: $67,454

GDP per Capita: $148,538
Mortgage Risk: 3.9355
Average Disposable Income: $118,504

Several counties in the bay area made the cut. This analysis is comprised of the following counties: Marin, San Mateo, Santa Clara, San Francisco.

It’s not a common thought to think of the bay area as livable with their housing crisis and homeless problem the area faces; however, looking at the data shows that those employed (especially in the booming tech industry) are able to fully utilize everything the area has to offer.

The bay area has the highest average household income on the list as well as the highest GDP per capita. The affordability of the city plays a heavy role with the fact that this area has the highest difference between income and discretionary income.

7. Indianapolis – Hamilton County

Population: 353,562
Average HH Income: $134,750
Average Discretionary Income: $68,669

GDP per Capita: $81,691
Mortgage Risk: 2.7086
Average Disposable Income: $97,894

Hamilton County is what you can consider a “healthy economy.” Their economic vitality score places them right on par with the national average. This along with high spending potential make it a solid area to live.

6. Forsyth County, GA

Population: 253,007
Average HH Income: $130,218
Average Discretionary Income: $69,663

GDP per Capita: $81,203
Mortgage Risk: 3.0771
Average Disposable Income: $100,934

Although this is the most rural county on our list, their incomes and spending power allow them to put up a good fight. Forsyth County has the highest economic vitality index on the list but the lowest GDP per capita.

5. New Jersey (New York Suburbs)

Population: 824,369
Average HH Income: $157,070
Average Discretionary Income: $69,707

GDP per Capita: $106,938
Mortgage Risk: 2.8996
Average Disposable Income: $108,721

This is another area with several counties making this top cities list. The counties included are Morris and Somerset.

A commute from a Jersey town to the bustling island of Manhattan is a pop culture reference at this point. With their close proximity to high incomes and the availability of more affordable real estate, it’s not hard to believe these counties host some of the most livable cities.

4. Baltimore – Howard County

Population: 330,939
Average HH Income: $151,890
Average Discretionary Income: $71,558

GDP per Capita: $90,908
Mortgage Risk: 3.2304
Average Disposable Income: $110,736

This county has an advantage that no other county on this list has. This county is sandwiched between two major metropolitan cities (Baltimore being the closest). The residents of this county get to benefit from both Washington D.C. and Baltimore.

3. Washington D.C. – Loudoun and Fairfax County

Population: 1,556,521
Average HH Income: $164,066
Average Discretionary Income: $73,537

GDP per Capita: $92,160
Mortgage Risk: 3.4726
Average Disposable Income: $116,647

The capitol city is hosting quite a few different neighboring counties on this list. Loudoun and Fairfax are benefitting from the city the most. These counties are enjoying healthy economies. The discretionary incomes in these areas are mirroring some people’s entire income.

2. Denver – Douglas County

Population: 367,726
Average HH Income: $150,232
Average Discretionary Income: $74,097

GDP per Capita: $81,981
Mortgage Risk :3.4863
Average Disposable Income: $110,941

For a city of its size, Denver has a relatively high cost of living. That does come with some great salaries. The neighboring counties, like Douglas, are the ones taking the most advantage of that.

The most livable county in America:

1. Nashville – Williamson County

Population: 250,620
Average HH Income: $153,023
Average Discretionary Income: $78,515

GDP per Capita: $98,173
Mortgage Risk: 3.2665
Average Disposable Income: $112,789

Austin didn’t make the top 10 in a city list? Not this time. A Nashville county currently holds the rank as the most livable city in America according to our discretionary income data. Between the cost of living and the cost of real estate in Tennessee, residents are able to afford to shop and spend lavishly.

Everyone’s definition of the most livable city/county will be different. Spending on necessities takes a large portion of our annual salaries. The money that is left over is what we can spend on pleasantries and entertainment like vacations, luxury goods, gifts, etc. Having the ability to spend on activities and goods like that are what make cities livable and popular.

Using variables like discretionary income and comparing them to staple variables like household income and mortgage risk can make for effective customer profiles and city stories. Combining different datasets and cross analyzing data is how you make effective and profitable site-location and related decisions.

STI: PopStats and STI: Spending Patterns made this analysis possible. Contact us to learn how you can put our data to work for you.

Put Data into Action

The Synergos 2020 Census Plan

What you can expect from your data partners with the 2020 Census.

The Synergos 2020 Census Plan

What you can expect from your data partners with the 2020 Census.

October 19, 2021 Update

As the Census Bureau continues to work through its releases, we wanted to update you on their status and how their past and future releases are incorporated into our products. We put together this Q&A to address most of your questions regarding the process and our updated schedule for fully incorporating the 2020 Census and releasing estimates with 2020 geographies. Please read carefully and don’t hesitate to reach out should you need clarification or further discussion on any point.

What Census 2020 data has been released?

The first 2020 Census data released by the Census Bureau in late April 2021 included only Population counts on a State level of geography. Then in August 2021 they released the redistricting data, also known as the P.L. 94 data. This data was released in other formats in mid-September. The P.L. 94 data includes fields for Population, Race, Ethnicity, Housing units, and Voting Age at a Census Block level of geography.

How has that data been incorporated into PopStats?

The first incorporation was with our July 2021 release. We used the Census 2020 state-level figures to adjust our county-level control population totals. With the latest October 2021 release, we have used the P.L. 94 data to adjust the county-level control population totals. This integration method has kept our models based on 2010 geographies but still allows for some adjustment based upon the 2020 Census data. Most areas saw only slight changes. Areas that saw more effect were areas like New Jersey, which we undercounted compared to the 2020 Census, and Arizona, which we overcounted.

What data are we waiting on for a full rebuild based upon 2020 geographies and lower-level data?

The Demographic and Housing Characteristics File (DHC) includes data that in 2010 was previously included in the SF1 file. This data includes several key breakouts that are necessary for rebuilding our estimate models based on the new 2020 geographies. These include households, age, sex, race, and their cross tables, among others. The household count and other detailed breakout fields are imperative to rebuild the estimate model. It should be noted that the P.L. 94 data does not contain a household count and many other critical breakouts.

What is the current estimated timeline for a complete 2020 based version?

The Census Bureau does not have a precise date set for the release of the DHC and Detailed DHC and never has given one. Previously the rumors, among mostly state demographers with which the Census coordinates, indicated state-by-state releases from late August 2021 through December 2021. Based upon this we have currently and tentatively set our 2020 update schedule for the April and July releases in 2022. However, none of those files have been released to date. Currently, they list “Tentatively 2022” on the main Census 2020 web page. And in the Stakeholder Engagement plans just released in September there is slightly more detail for the DHC timeline. This source indicates that the DHC will “Begin Production”, after two rounds of format and privacy review and public comment that are to occur in Winter and Spring. This timeline indicates they will start producing the DHC files in Summer 2022. If that is the case, and we really hope it isn’t, we will make every attempt to meet an October 2022 release.

How does this compare to the 2010 Census release?

The SF1 file for the 2010 Census had several versions. The first version was a state-by-state release that occurred between June and August 2011. This allowed us to have our conversion to the 2010 geographies completed by the October 2011 release. If the Census Bureau releases the DHC data around June that will be about a year behind how the 2010 Census release went.

Why the delay?

The Census Bureau had a major early issue with conducting the 2020 Census, the Covid-19 pandemic. The ultimate effects of this were a delay of only a few months. An impressive testament to the Census Bureau’s ability to adapt. This is why we, along with other industry demographers, expected state-by-state releases between August and December 2021. Just a slightly lagged version of the 2010 SF1 file release schedule. That was until last month’s Stakeholder Engagement plans indicated that this data would not be released until it could be revised for differential privacy noise injection, which is the bureau’s new additional mechanism for keeping personally identifiable information confidential. This will end up further delaying an already late release.

We were the first demographic data company to release a 2010 Census based estimate, and we’re committed to leading the pack in releasing accurate estimates with the 2020 Census. We appreciate that you chose Synergos products because of our uncompromising commitment to quality and the timeliness of our releases, and we are eager to continue to prove our value as we work towards a 2020 Census based estimate.

If you have any questions, please don’t hesitate to give us a call at (512) 343-1963 or simply chat with us right here.

Curious about PopStats? Reach out and we’d be glad to help!

Learn More Census Bureau Website

Recerational Equipment, Inc. (REI)

REI Accelerates New Store Openings with PopStats and LandScape

Recerational Equipment, Inc.

REI Accelerates New Store Openings with PopStats and LandScape

It would be easier for Recreational Equipment Inc. to use another data provider’s dataset because the company that creates their sales forecast models uses it. However, Curt Newsome, REI’s real estate research and strategy manager, said, “I don’t care. I want to use PopStats and LandScape.”

He prefers PopStats and the LandScape neighborhood segmentation dataset for two main reasons: “PopStats is high-quality data and the company is accessible. If I have a question about the data, I can call and get an answer. The team there is very accessible and supportive. I don’t get shuffled to people who don’t have answers. In fact, they often give me more detail than I can absorb.”

“That’s important to me because I’ve worked with lesser quality data and it’s a case of ‘you get what you pay for.’” Curt added: “… data isn’t just a sideline for them. It’s their core. They know their methodology inside and out. That’s why they have the best reputation in the business.”

Quality data that he can depend on is critical to Curt’s research success, in particular, because REI only opens a few new stores each year. As a result, they have to be in the exact right locations.

“Our store location history has gone through many phases, including having no strategy whatsoever and letting real estate brokers decide where we’ll open stores. Now, we’re in the ‘age of enlightenment,’ where we open new stores based on both the science of analyzing revenue potential and the art of our real-world experience.”

In particular, one of the organization’s goals is to make REI better known outside of the West Coast, where it originated. More than a third of REI stores are in California, Oregon, and Washington. However, the company has since expanded into new markets like Jacksonville, Fla., Kansas City, Mo., and Columbus, Ohio. Along with new locations, the company also began considering new store concepts and a separate strategy for more flagship locations.

STI: LandScape™ Correlates with REI Customers

Today, Curt relies on both PopStats and LandScape to scout new territories for new stores and assess the status of existing stores. “Our process begins with segmenting our target markets using LandScape, so we can create our forecast models. It’s our critical first step because REI’s customer profiles are extremely segmented in comparison to most other retailers.”

“LandScape segments do an incredible job of correlating to our ideal customer segments,” said Curt. “In fact, the 72 segments’ correlations are so meaningful to REI that the company will ignore a lower population count in a market if it finds a large enough population of its ideal segments.

“LandScape allows us to perform a unique calculation to understand a market with different demographic qualities,” notes Curt. “That’s why it’s become one of the key building blocks in our models when we are researching trade areas where we don’t already have stores.”

Before applying LandScape data to its research, REI processed a year’s worth of transactional data — about one million records — including every sale and every return. It geo-tagged each data point. That showed them where members live, where members shop, and what they buy.

By mapping that data against the retailer’s dominant cluster data, REI was able to assign a score for all 72 segments in LandScape on the segments’ propensity to shop at REI. That allows the company to, simply stated, assign a score to any geographic area and gauge how likely REI is to be successful there. “It’s just as important to know all the segments that score low as to know all of the segments that score high.”

About 15 segments in LandScape deliver the highest probability of being REI customers. However, Curt stresses: “That doesn’t mean that we’ll only put stores where those consumers live. There are many other factors that we consider as well.”

Among the other factors, we are looking at alternative sites where there is no residential customer base. Instead, it’s a place that people travel to for outdoor recreation, like Conway, New Hampshire, and Dylan, Colorado. “Since we’re running out of standard places to open new stores, we’re expanding our search into alternative store locations and types,” explained Curt.

Applying Art and Sciene to Trade Area Analysis

After forecasting its customer segments, Curt moves onto trade area analysis, relying on PopStats to compile relevant data on each trade area’s demographic characteristics. “The purpose of this analysis is to determine if a strategically validated relationship exists between the site’s attributes and our ideal store performance.”

REI’s site analysis includes three typical scenarios:

Model Validation – In a normal trade area, “we track the prediction using variables such as trade area capture rates, sales per population, and total sales per household.”
Increase Forecast – Some markets need a manual boost in estimates for a variety of reasons, such as Burlington, Vermont. “Not surprisingly, REI’s capture rate is very high there,” noted Newsome. “Almost everyone is a potential customer. Plus, we get a bump from the local university.”
Decrease Forecast – If a market looks different demographically or has a lower population, Newsome will manually lower the forecast. “For example, in Salem, Oregon we decided to open a smaller store. Today, it’s a good steady performer.”

So how accurate is REI’s new market analysis processes? “We haven’t measured the raw model yet, but we’ve opened about 30 new stores using this methodology. We’ve only under predicted by about three percent of the time, which is great compared to the industry standard of 15 percent.”

Interestingly, in REI’s over 80-year history the company has rarely closed a store. But in 2015 the company closed its first one and has relocated a couple of stores since then. Newsome is so confident with his current research process that he says: “If we had the model we have now when he opened that now-closed store, we never would have opened it in the first place.”

Backed by trade area research it can trust, REI plans to continue opening new stores at a pace of anywhere from two to 12 per year.

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Brixmor Property Group

PopStats Helps Brixmor Lease Millions of Square Feet

Brixmor Property Group

PopStats Helps Brixmore Lease Millions of Square Feet

Not only does Brixmor use PopStats data, but also the firm has invested in three other products in the PopStats data suite: STI: Market Outlook, STI: Spending Patterns, and STI: WorkPlace.

After years of successfully executing real estate leasing, acquisitions, and development projects across the country without a dedicated market research department, in 2014 Brixmor decided to expand its research capabilities to help drive leasing efforts at its centers.

The first step in its expansion was hiring a Director of Research. Brixmor found the perfect candidate in David Spawn. Brixmor, in turn, found the right demographic data when they selected Trade Area Systems to execute its market analysis using STI: PopStats.

We needed to hit the ground running in order to demonstrate the value in our new operation. PopStats allowed us to move quickly,” said David. “Today Brixmor uses PopStats on most of its projects.”

Supporting Sales with Data Options

As a real estate investment trust (REIT), Brixmor owns and operates a high-quality, national portfolio of open-air shopping centers. Its 400-plus retail centers comprise approximately 73 million square feet of prime retail space in established trade areas.

The company strives to own and operate shopping centers that reflect Brixmor’s vision “to be the center of the communities we serve.” Those communities are home to a diverse mix of national, regional, and local retailers — including The TJX Companies, The Kroger Co., Publix Super Markets, Wal-Mart, Ross Stores, and L.A. Fitness.

Before the new research department could prove its overall success, it educated the company’s team members in a series of education sessions on how to use and maximize the impact of the new market research tools. In addition to the leasing team of 65-plus agents located in NYC and 10 regional offices, other internal clients included Brixmor’s acquisition and disposition team.

Market Outlook: A Popular Dataset

“Among all of the data variables we now offer our agents in the PopStat suite, Market Outlook’s gap analysis has proven to be many agents’ favorite data,” noted David. “With this data, they can show prospective tenants what the market potential is and what the gaps are in consumer spending in those areas.”

Retailers can leverage the Market Outlook insight to rent space in one of the company’s properties and begin meeting the existing consumer demand with their products and services.

“When our agents share insights beyond population counts and other demographic data, such as the gap between consumer demand and spending in everything from home furnishings to apparel to groceries, it makes a huge impression,” explains David. “Needless to say, Market Outlook has been a big hit in our company.”

Spending Patterns is a Huge Asset

Spending Patterns has also been a huge asset to the real estate leasing processing, added David. “Even if the population count is on the low end and we can’t show the potential client a huge supply and demand gap, we may be able to show them that consumers are still spending a lot in a particular sector. That kind of data makes a great story as well.

“Our access to such a robust variety of datasets gives us a wide range of data to pull from when our agents are in the midst of real estate negotiations,” notes David. “There may be more than one way to demonstrate the potential value of a single property, and we want to be able to give them all of the tools in the toolbox.”

Brixmor’s addition of market research to its internal operations is paying off and helping the firm meet its mission: To be the center of its communities by matching vibrant retail to local culture and needs. Market research is helping the company meet and exceed its business goals.

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Weingarten Realty

Weingarten Realty Enjoys Utmost Confidence in the STI: PopStats™ Estimates

Weingarten Realty

Weingarten Realty Enjoys Utmost Confidence in the STI: PopStats™ Estimates

Confidence is the number one benefit Weingarten Realty receives from STI: PopStats’ quarterly population estimates, says the company.

Weingarten’s confidence in the accuracy of STI: PopStats began with its first look at the demographic data in an Arizona test market. “PopStats picked up people that we otherwise would have missed,” says Kyle Kretsinger, Director of Research/Marketing Services for the commercial real estate company based in Houston, Texas.

“In fact, another data vendor’s product missed this population entirely in a side-by-side comparison,” Kyle adds. While the population estimates from the other data provider showed no population in both one-mile and two-mile trade area rings, PopStats estimated 3,000 and 6,000 people respectively. “These numbers are significant. They can make or break a new project.”

Weingarten’s confidence has only gotten stronger since its introduction to PopStats data — which has helped the company not only make better decisions but also save money.

Saving Research Costs

“Our confidence in PopStats’ numbers is so high that we greatly reduced the number of housing studies we conducted in growth markets,” explains Kretsinger.

Typically, the real estate development company surveyed homebuilders that were building new subdivisions in new markets. The price tag for these in-field services was anywhere from $4,000 to $8,000, depending on if Weingarten conducted the research itself or used a third-party research firm. They were a significant expense, with up to 20 housing studies a year conducted when the company was focused on new developments.

“Even if we conducted the research ourselves, there are many costs, including airfare, hotels, meals, and time out of the office,” notes Kyle.

“After we started using PopStats we were able to replace most housing studies with PopStats’ quarterly growth trends — that’s how certain we are of the data’s ability to see populations in markets as they are growing.”

“PopStats has the unique ability to give us a very high comfort level without needing to spend the money to feel comfortable with our decisions,” adds Kyle.

Gaining Workplace and Seasonal Insight

Along with saving on housing studies, Kyle says that PopStats data has also saved the company the expense of conducting workplace studies. “We used to go into new markets and count how many businesses were there. Then apply a formula to determine how many people worked in the area. The number is important to our clients who rely on a certain percentage of daytime population for their business operations.

“Now, PopStats provides us with accurate workplace population counts — which we also have the utmost confidence in. This is another great convenience and savings.”

With several shopping centers located in the Southern part of the U.S., seasonal population trends are also a valuable form of demographic insight for Weingarten, notes Kyle. “PopStats is the only data that allows us to track seasonal trends. With its quarterly population updates, we are able to clearly see the seasonal fluctuations in our markets. We can share this insight with our tenants, so they can make more informed business decisions as well.”

Speaking the Same Language

With the high-growth boom on hold for the time being, Weingarten is focused on managing the property it currently owns. This includes marketing its existing space to retailers. “PopStats data comes in handy for marketing our properties,” notes Kyle. “We can show potential clients what population exists and what changes are expected. All companies do a better job when they understand the dynamics of a trade area’s population.”

Kyle notes that many of Weingarten’s larger retail clients like grocers and restaurants already use PopStats data in their own market research activities. “This is great because we are all speaking the same language when discussing population counts and characteristics.”

To gain utmost confidence in your market research like Weingarten, contact Synergos Technologies today about the STI: PopStats data suite today.

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The Highest Home Values in Texas

In a market this hot, which county is the hottest?

The Highest Home Values in Texas

In a market this hot, which county is the hottest?

Being that Texas is as large as it is, the lone star state’s home values can vary vastly across the market. According to PopStats data, the average Texas home value in January 2021 was $280,816. Some counties blow that number out of the water. Let’s take a closer look at the top 10 counties with the highest home values.

All numbers and figures used were created using STI: PopStats™ data. Contact us to learn about the thousands of other variables we update quarterly.

Top 10 Counties With the Highest Home Values

10. Bexar County (Primarily San Antonio)

Population: 2,063,682

2021 Average Home Value: $248,578
2020 Average Home Value: $238,003

Average Household Income: $82,607

San Antonio is the major city for Bexar County and sits at number 10 on our list for home values. The counties that are listed higher are counties of the 3 other major cities of Texas, and the counties that make up their suburbs. San Antonio just so happens to also rank number 10 in Texas counties for average household income.

9. Harris County (Primarily Houston)

Population: 4,720,553

2021 Average Home Value: $294,658
2020 Average Home Value: $285,051

Average Household Income: $96,504

Harris County is a massive county in that it encompasses all of Houston (the 4th most populous city in the United States) as well as a few of Houston’s suburbs including Katy, Baytown, Friendswood, etc. The size of Harris County attributes to its status as the most populated county in the state, as well as the 3rd most populated county in all of the United States.

8. Dallas County (Primarily Dallas)

Population: 2,617,867

2021 Average Home Value: $344,135
2020 Average Home Value: $332,705

Average Household Income: $94,526

Dallas County is self-explanatory in its name. Although Dallas ranks in the top 10 of Texas counties in home values, its suburbs dominate several rankings in this category.

7. Tarrant County (Primarily Fort Worth)

Population: 2,111,344

2021 Average Home Value: $300,664
2020 Average Home Value: $289,162

Average Household Income: $96,056

People living in Dallas County (more specifically Dallas) may be living there for the amenities that larger cities offer like job opportunities, nightlife, entertainment, etc. Within the same metro, although smaller and not as vast, is another large city that offers similar amenities – Fort Worth. Ranking 7 in our list, people living in Tarrant county can experience similar amenities, as well as higher home values and better household incomes.

6. Montgomery County (Houston Suburb)

Population: 630,248

2021 Average Home Value: $338,042
2020 Average Home Value: $327,020

Average Household Income: $117,377

Our first suburb on the list and it’s one that sits right outside of the massive city that is Houston, Texas. This county is bliss suburbia in that it enjoys having close access to city amenities like incomes, jobs, and entertainment, while also maintaining a healthy housing market.

5. Fort Bend County (Houston Suburb)

Population: 839,981

2021 Average Home Value: $339,863
2020 Average Home Value: $328,781

Average Household Income: $127,003

Another Houston suburb making the list, but this time in the southwestern part of the Houston metro. Fort Bend County only offers slightly higher home values than Montgomery County but boasts a significant higher population.

4. Williamson County (Austin Suburb)

Population: 635,242

2021 Average Home Value: $390,100
2020 Average Home Value: $365,462

Average Household Income: $110,183

Our first mention of Austin on this list and it’s one of the suburb counties. This county’s home values are rising even faster than Austin’s! But only barely. With a 1 year change of 6.7416% increase over last year, Williamson County is doubling the national average in rising home values.

So far, we have mentioned most of the major counties in Texas and a few of their suburbs. With only 3 left in our top 10, keep reading to find out which counties have the highest home values in the state of Texas.

3. Denton County (Dallas Suburb)

Population: 924,022

2021 Average Home Value: $396,122
2020 Average Home Value: $382,967

Average Household Income: $117,656

Our first Dallas suburb hitting the list enjoying similar benefits as Houston’s suburbs. With an average drive time of 45 minutes to get to downtown Dallas, living in Denton is very advantageous for a variety of different households.

2. Collin County (Dallas Suburb)

Population: 1,072,393

2021 Average Home Value: $437,460
2020 Average Home Value: $422,931

Average Household Income: $117,656

2 of the 3 counties in Texas with the highest home values are both Dallas suburbs. It makes sense with how the DFW metropolitan area offers numerous job and travel options to many industries.

The Texas county with the highest home values is:

1. Travis County (Primarily Austin)

Population: 1,329,463

2021 Average Home Value: $536,117
2020 Average Home Value: $502,257

Average Household Income: $116,445

Out of every county in Texas, Travis County has the highest home values out of all of them! They aren’t just the highest, they’re all growing at an exceptional rate. The Travis County market is growing 78% faster than the national average. Many factors are contributing to this like a booming tech industry, a large number of entertainment jobs, and they are consistently making it on our annual top growth markets report.

Travis is the only major county to beat its metro counties, and it beats them in both home values and income. Travis County is the county to look at in Texas for growth and innovation.

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