What do we mean by a neighborhood?
NeighborhoodScout® uses the official government designation for neighborhoods - the census tract.
Census tracts are small, relatively permanent subdivisions of a county that are defined by the U.S. Census Bureau in conjunction with local authorities all across the country to define real neighborhoods that are bounded to contain areas with homogeneous population characteristics (including economic status, lifestyle, and living conditions). Census tracts usually have 4,000 persons, but can range between 1,500 and 8,000 persons. This is the most fine-grained area for which detailed information is made available from the government, to protect the individual privacy of each of us. Because census tracts are based on population, they vary in size depending on the density of settlement. In urban areas, they are small, and in rural areas they can cover an entire small town or even a few small towns in very rural areas.
Since census tracts are subdivisions of a county, we did a spatial overlay of the census tracts onto city and town boundaries using a geographic information system to properly assign each census tract to its appropriate city or town. Then we named each census tract to the local colloquially recognized neighborhood name for that spot (e.g., Boston, MA (Dorchester). If there was not a name available, we named the census tract by the largest street intersection in the census tract (e.g., Worcester, MA (Lincoln St/Plantation St)
Why we don't use Zip Codes as neighborhoods
Zip codes were developed by the Postal Service for the purpose of delivering mail, but were never intended to define coherent neighborhoods. In addition, Zip Codes can have as many as 10 distinctly different census tracts contained within them. When distinct census tracts are blended together in a single Zip Code, the data reflects their average conditions and often gives a false sense of the area. The result is that potentially great matching neighborhoods can be missed, and erroneous matches can also be produced and delivered to you.
Using census tracts makes great matches possible, and helps people find the areas that are best for them and their families. Because we are committed to providing the highest possible quality and finding the neighborhoods that best meet your criteria, we use census tracts. And, as always, we show you the actual street map of the neighborhood so you know exactly where your best matching neighborhood is located.
What is a Condition Alert?
A condition alert is a condition in the neighborhood that triggers an alert. NeighborhoodScout contains condition alerts to highlight conditions that are extreme, whether good or bad. This helps answer crucial questions about the state of the neighborhood being evaluated, such as:
What are the risks of violent crime here?
Is the risk of home break-ins or other property crimes increasing?
Does real estate here hold its value?
Are the trends in local vacancies or unemployment concerning?
...and dozens more.
Information at a glance that you need to know to invest, appraise or finance a property.
Seffner Community Alliance median real estate price is $330,328, which is less expensive than 68.5% of Florida neighborhoods and 55.7% of all U.S. neighborhoods.
The average rental price in Seffner Community Alliance is currently $2,228, based on NeighborhoodScout's exclusive analysis. Rents here are currently lower in price than 67.1% of Florida neighborhoods.
Seffner Community Alliance is a suburban neighborhood (based on population density) located in Mango, Florida.
Seffner Community Alliance real estate is primarily made up of medium sized (three or four bedroom) to small (studio to two bedroom) single-family homes and small apartment buildings. Most of the residential real estate is occupied by a mixture of owners and renters. Many of the residences in the Seffner Community Alliance neighborhood are established but not old, having been built between 1970 and 1999. A number of residences were also built between 2000 and the present.
Home and apartment vacancy rates are 8.2% in Seffner Community Alliance. NeighborhoodScout analysis shows that this rate is lower than 46.8% of the neighborhoods in the nation, approximately near the middle range for vacancies.
Notable & Unique Neighborhood Characteristics
Many things matter about a neighborhood, but the first thing most people notice is the way a neighborhood looks and its particular character. For example, one might notice whether the buildings all date from a certain time period or whether shop signs are in multiple languages. This particular neighborhood in Mango, the Seffner Community Alliance neighborhood, has some outstanding things about the way it looks and its way of life that are worth highlighting.
Occupations
With 2.2% of employed workers living in the Seffner Community Alliance neighborhood active in the military, this neighborhood has the distinction of having a higher proportion of people in the military than 96.7% of American neighborhoods. This is a major shaper of the neighborhood's culture and character.
Furthermore, from major sales accounts to fast-food workers, sales and service employees are often the backbone of the local economy. In the Seffner Community Alliance neighborhood, they truly stand out. NeighborhoodScout's exclusive analysis identifies this neighborhood as having a higher percentage of sales and service workers than 95.2% of all American neighborhoods.
Modes of Transportation
If your dream is to be able to ride your bike to work each day, look no further than this unique neighborhood. With 3.4% of residents in the Seffner Community Alliance neighborhood commuting on a bicycle to and from work daily, this neighborhood has more bicycle commuters than 96.4% of all neighborhoods in the U.S., according to NeighborhoodScout's exclusive analysis.
Diversity
Did you know that the Seffner Community Alliance neighborhood has more Puerto Rican and Dominican ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 12.2% of this neighborhood's residents have Puerto Rican ancestry and 3.8% have Dominican ancestry.
The Neighbors
There are two complementary measures for understanding the income of a neighborhood's residents: the average and the extremes. While a neighborhood may be relatively wealthy overall, it is equally important to understand the rate of people - particularly children - who are living at or below the federal poverty line, which is extremely low income. Some neighborhoods with a lower average income may actually have a lower childhood poverty rate than another with a higher average income, and this helps us understand the conditions and character of a neighborhood.
The neighbors in the Seffner Community Alliance neighborhood in Mango are low income, making it among the lowest income neighborhoods in America. NeighborhoodScout's research shows that this neighborhood has an income lower than 87.5% of U.S. neighborhoods. With 26.0% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 76.7% of U.S. neighborhoods.
The old saying "you are what you eat" is true. But it is also true that you are what you do for a living. The types of occupations your neighbors have shape their character, and together as a group, their collective occupations shape the culture of a place.
In the Seffner Community Alliance neighborhood, 38.1% of the working population is employed in sales and service jobs, from major sales accounts, to working in fast food restaurants. The second most important occupational group in this neighborhood is executive, management, and professional occupations, with 29.6% of the residents employed. Other residents here are employed in manufacturing and laborer occupations (18.8%), and 11.7% in clerical, assistant, and tech support occupations.
Languages
The most common language spoken in the Seffner Community Alliance neighborhood is English, spoken by 73.9% of households. Some people also speak Spanish (19.6%).
Ethnicity / Ancestry
Boston's Beacon Hill blue-blood streets, Brooklyn's Orthodox Jewish enclaves, Los Angeles' Persian neighborhoods. Each has its own culture derived primarily from the ancestries and culture of the residents who call these neighborhoods home. Likewise, each neighborhood in America has its own culture – some more unique than others – based on lifestyle, occupations, the types of households – and importantly – on the ethnicities and ancestries of the people who live in the neighborhood. Understanding where people came from, who their grandparents or great-grandparents were, can help you understand how a neighborhood is today.
In the Seffner Community Alliance neighborhood in Mango, FL, residents most commonly identify their ethnicity or ancestry as German (13.5%). There are also a number of people of Puerto Rican ancestry (12.2%), and residents who report Irish roots (6.4%), and some of the residents are also of Italian ancestry (5.8%), along with some Asian ancestry residents (5.0%), among others.
Getting to Work
How you get to work – car, bus, train or other means – and how much of your day it takes to do so is a large quality of life and financial issue. Especially with gasoline prices rising and expected to continue doing so, the length and means of one's commute can be a financial burden. Some neighborhoods are physically located so that many residents have to drive in their own car, others are set up so many walk to work, or can take a train, bus, or bike. The greatest number of commuters in Seffner Community Alliance neighborhood spend between 15 and 30 minutes commuting one-way to work (43.4% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (71.0%) drive alone in a private automobile to get to work. In addition, quite a number also carpool with coworkers, friends, or neighbors to get to work (5.9%) . In a neighborhood like this, as in most of the nation, many residents find owning a car useful for getting to work.
SCOUT’s patented match algorithm identifies the most similar neighborhoods to a subject location, and quantifies the similarity to the subject location. This allows analysts to identify the most similar neighborhoods in a local market area for appraisals, investments, and research.
The algorithm uses 273 neighborhood conditions, identifies the dominant dimensions underlying the conditions and calculates the similarity. This captures the true culture and character of locations, economic conditions, and trends.
The closer to 100% means the locations are nearly identical. 80% is a very good, but not excellent match, and so forth.
