Part 1: Demographics & Psychographics

Based on our last blog post we uncovered that Florida MSAs are experiencing rapid residential development, population growth, & migration. Among them is The Villages, FL MSA, who according to the census bureau is the fastest growing metro area in the nation with a population increase of nearly 5% from 2022 to 2023. Our residential development data highlights this MSA with 28 homes/sq. mi being built 2019-2023, 10 homes/sq. mi actively being built, and a whopping 174 homes/sq. mi planned. This growing metro is in central Florida in between Tampa Metro and Ocala metro. Now let’s look at demographics and psychographics to better understand the population that makes up this MSA.

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              The Villages, FL MSA is far less populous than other Florida MSAs by almost 90%. With a low population density when compared to the state and other Florida MSAs (-37%and -54% respectively), the area provides opportunity for development and growth. It is then no surprise that the projected population growth for the next 3 years (2023-2026) is significantly higher when compared to the state and other Florida MSAs by over 200% and 150% respectively. Households have a slightly higher median income, and with median home values of $366K, The Villages, FL can be considered more affluent when compared to the State and other Florida MSAs. The population is also generally much older and predominately white.

We can begin to understand more about this metro area by looking at the overall demographics but from a retailer’s perspective do we know anything about their shopping patterns, social media interests, and general appetite for a brand like yours? TSCG Analytics can add that detail, using psychographics like Spatial.ai’s PersonaLive dataset we can better understand who lives in this quickly expanding area. This insight is crucial in understanding if it is the perfect audience for your brand to serve. Psychographic data gives insight into in-store, web, and social media visitation behaviors for these households, which can help retailers best position themselves to serve their surrounding communities. This data can serve purposes beyond site selection and aid in proper store merchandising and target marketing.

The overwhelming majority of households in this MSA belong to the Snowbird Set segment with almost 30K households making up 52% of all households in this MSA, followed by Couples Coasting In with 10.5K households (19%), and Merica with 3K households (5%). The Snowbird Set segment is described as modestly retired couples, many living in Florida, these households spend time thinking about their next vacation to the beach or casino. Mainly white and conservative, they watch Fox & Friends (and The View) and follow personalities Greta Van Susteren and David A. Clarke, Jr. Hashtags include #coastalliving, #sunglasses, and #cruise. This segment’s median age is 69, median household income of $49K, 45% are married, and a majority are homeowners. This aligns with the demographic profile of the MSA, validating this segment's population majority in the area. Where Psychographics shine is in the additional insights we can glean, in the table breakdown below of their top in-store visitation patterns: Snowbird Set Households are 6.88x more likely to visit an Edwin Watts Golf Shop than other segments in the Southeast, 5.87x more likely to visit US Eye location, and 5.82x more likely to visit Scooter’s Coffee. Not only are these strong signals of brand/concept loyalty it gives us greater insight into the types of services and retail this segment is overwhelming drawn to.

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Furthermore, the Snowbird Set household has a high likelihood to follow travel, grocery, and home social media accounts among the top accounts being Publix (4.7x), Cruise Norwegian (2.3x), & Trulia (2.3x). They are most likely to visit travel websites and are 3.7x more likely visits websites for Palm Beach Vacations, and 2.9x more likely to visit Hard Rock Hotel & Casino websites.

Part 2: Retail Landscape

Now that we understand the households that make up this metro, what can we learn from the existing retail landscape and how can that inform which concepts might benefit from opening a location here?

When analyzing all chains that have been tracked for the past year within the MSA we see that chains have experienced a growth of 11% this is higher than the state average for the same period of 5%.

By analyzing visitation to shopping centers within the main retail corridor and if they have experienced visitation growth helps define the health of retail within the market. By looking at the sum of visitation to the 16 shopping centers within the market by year there is a positive trend of visitation growth, with 2023 visitation surpassing pre-covid numbers. This tells us that the shopping centers are experiencing healthy growth in traffic and with the development of 174 homes/sq mi planned it is very likely to continue increasing.

This growth will likely increase the demand for more of those top brands and categories the snowbird household is interested in such as golfing retailers/other lifetime sports retailers, Restaurants with a strong affinity for coffee shops, and medical retailers such as dentist offices, eye care, and hearing aid retailers. These types of retailers and restaurants may want to consider a strategy of opening a location in this market. For example, as far as coffee shop concepts the main chains that exist are Dunkin’ Donuts and Starbucks. The most visited Starbucks in this market located at 874 U.S. 27/441, Lady Lake, FL is among the top 82% Starbucks in the nation in terms of estimated sales, grossing about $3 million in the past 12 months. This could be an opportunity for a Scooter’s Coffee location, to serve a new market, that has shown to have an affinity for the brand (5.8x more likely to visit), and where other chains are performing well.  

From the perspective of leasing teams & asset managers, a critical part of maintaining a strong shopping center is being in tune with what the surrounding community desires and needs while being able to attract tenants that can support those. For shopping centers operating in the villages metro this could mean assessing if there is a nearby coffee shop and if not attracting one. This could make all the difference between someone going to one shopping center vs another. If they can also pickup coffee on their way to your center, it provides convenience and synergy for that customer’s journey. Similarly, a shopping center might consider attracting a golf concept whether that be a retailer like Edwin Watts or a fitness concept like GOLFTEC.

In today’s competitive retail landscape, data-driven decision-making is crucial for success. Whether you’re a retailer, a restaurant chain, or a property manager, understanding the data can significantly impact your site selection and leasing strategies. Here are some key considerations:

Demographic Insights:

·       Household Composition: Analyze the demographics of the local population. Understand the mix of families, retirees, and other groups. For instance, in The Villages metro area, we’ve identified snowbird set households as a significant segment.

·       Income Levels: Look at income distribution. High-income areas might support luxury brands, while middle-income neighborhoods may be ideal for mid-tier retailers.

·       Age and Lifestyle: Consider the age groups prevalent in the area. Are there young professionals, families, or retirees? Their preferences and needs vary, affecting the types of businesses that thrive.

Foot Traffic and Visitation Patterns:

·       Shopping Center Traffic: Use foot traffic data to evaluate the health of existing shopping centers. Are they attracting visitors consistently? Analyze trends over time.

·       Peak Hours: Identify peak hours for foot traffic. This information helps retailers optimize staffing and promotional activities.

·       Competitor Proximity: Understand where competitors are located. Sometimes being near a competitor can be advantageous (e.g., coffee shops near Starbucks), while other times differentiation is key.

Sales Performance and Brand Affinity:

·       Sales Data: Dive into sales data for existing chains. Which locations perform exceptionally well? What factors contribute to their success?

·       Brand Affinity: Identify brands that resonate with the community. For example, the high-performing Starbucks in The Villages suggests an affinity for coffee culture. Other chains can leverage this insight.

Gap Analysis:

·       Identify Gaps: Pinpoint gaps in the market. Are there underserved categories or concepts? Perhaps there’s a lack of specialty stores, fitness centers, or certain cuisines.

·       Opportunity Zones: Explore areas where demand exceeds supply. These are prime locations for new ventures.

Community Needs and Synergy:

·       Community Desires: Understand what the community desires. Conduct surveys or engage with local residents. Is there demand for a specific type of business?

·       Synergy: Consider how tenants complement each other. A coffee shop near a fitness center or a golf retailer near a sports bar creates synergy and enhances the overall shopping experience.

Predictive Modeling:

·       Predictive Analytics: Leverage predictive models to forecast future trends. Factors like population growth, housing developments, and economic indicators can guide decisions.

·       Scenario Testing: Run scenarios to evaluate different site options. What if you open near a retirement community versus a university campus? Simulate outcomes.

In summary, data analysis empowers businesses to make informed choices. Whether you’re selecting a site for a new venture or optimizing leasing decisions, harnessing data ensures that you align with community needs, capitalize on trends, and create successful retail spaces.

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