Rental market snapshot for Fairburn, Georgia

Fairburn, Georgia Rental Property Market Overview

The average rent for an apartment in Fairburn is $2,085. The cost of rent varies depending on several factors, including location, size, and quality.

The average rent has increased by 1.3% over the past year.

Fairburn is a city in Fulton County, Georgia, United States. It is part of the Atlanta metropolitan area. As of the 2010 census, the city had a population of 12,950.

Last Updated December 23, 2022

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Average monthly rent graph in Fairburn Georgia | Cost of Living

  • The most expensive ZIP Code in Fairburn is 30213 with an average price of $2,190
  • The cheapest ZIP Code in Fairburn is 30291 with an average price of $1,985

Fairburn ZIP Codes with the highest, most expensive rent

#zip codeaverage rent
130213$2,190
230213$2,180
330291$1,985

Live near Fairburn, Georgia's Top Sights and Attractions

Fairburn Nature Preserve is a beautiful nature preserve that offers hiking, biking, and picnicking opportunities. The preserve is home to a variety of wildlife, including deer, squirrels, and birds. The preserve is also home to a variety of plant life, including trees, flowers, and bushes.

Clarence Duncan Memorial Park is a beautiful park located in Fairburn, Georgia. The park features a playground, a walking trail, and a picnic area. The park is also home to a variety of birds and other wildlife.

Fairburn, Georgia area median rent change by ZIP Code map

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How does Fairburn compare to other cities in Georgia ?

citymedian price
Clarkston$1,350
Hiram$1,940
Midway$1,725
Martinez$1,600
Powder Springs$1,945
Lawreneville$1,755
Norcross$1,730
Grayson$1,960

Average household income in Fairburn area graph - US Census

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The median household income in Fairburn in 2021 was $55,198. This represents a 4.5% change from 2011 when the median was $52,839.

#categorypercent
0Less than $10,00010.4%
1$10,000 to $14,9992.2%
2$15,000 to $19,9997.4%
3$20,000 to $24,9996.4%
4$25,000 to $29,9996.6%
5$30,000 to $34,9990.8%
6$35,000 to $39,9992.2%
7$40,000 to $44,9998.4%
8$45,000 to $49,9994.0%
9$50,000 to $59,9994.7%
10$60,000 to $74,99910.3%
11$75,000 to $99,99913.4%
12$100,000 to $124,9996.3%
13$125,000 to $149,99910.6%
14$150,000 to $199,9994.4%
15$200,000 or more1.9%

Frequently asked questions

Our data is best categorized as "alternative data", which is a burgeoning sector. Through partnerships and direct feeds, we extract key factual elements that are publicly available within rental listings on internet listing sites and property websites. Once aggregated, we mine through the data to parse out relevant insights and calculate important metrics, benchmarks, and other KPIs. Each week, our system sifts through millions of listing observations and other pockets of market information to deliver the most comprehensive picture of rental housing available.

This is a metric that we try not to overthink. Simply, we take each unique listing observation within a geographic boundary and calculate a simple average. Of course, we're careful to filter for duplicates and other listings that aren't reflective of the market.

Yes, but please attribute us accordingly.

Yes. We can deliver bulk raw data in various formats. Please contact us to discuss - [email protected]

While some of our data is refreshed daily and other data comes in weekly, the bulk of it comes in on a biweekly basis.

Our coverage is nationwide! In our platform, we have data points for every ZIP code and neighborhood boundary in the country.

Every rental housing unit is differentiated by attributes such as its location, square footage, and amenity composition. Thanks to machine learning and natural language processing technologies we deploy, we're able to deconstruct our rental listing data points and identify key amenities for each listing. With this information, we're able to give signals around how certain amenities drive rental pricing value in certain areas.

Well, we think so! At the highest level, our process is simple. Listings data is ingested, cleaned (de-duplicated. etc.), analyzed for insights, and then presented to our users.
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