Rental market snapshot for Jackson, Georgia

Jackson, Georgia Rental Property Market Overview

The average rent for an apartment in Jackson is $1,541. The cost of rent varies depending on several factors, including location, size, and quality.

The average rent has increased by 6.2% over the past year.

Jackson, Georgia is a city located in Butts County, Georgia, United States. As of the 2010 census, the city had a population of 5,464. The city is the county seat of Butts County.

Last Updated December 23, 2022

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Average monthly rent graph in Jackson Georgia | Cost of Living

  • The most expensive ZIP Code in Jackson is 30233 with an average price of $1,615
  • The cheapest ZIP Code in Jackson is 30233 with an average price of $1,495

Jackson ZIP Codes with the highest, most expensive rent

#zip codeaverage rent
130233$1,615
230233$1,610

Live near Jackson, Georgia's Top Sights and Attractions

The Butts County Department Of Leisure Services is a great place to take the family for a day of fun. There is an outdoor pool, a playground, and a picnic area. The department also offers a variety of programs and events for the community.

High Falls State Park is a 3,502-acre state park located in Jackson, Georgia. The park is home to the tallest waterfall in the state of Georgia, which is High Falls. The park also offers camping, hiking, fishing, and picnicking.

Butts County Greenspace is a beautiful park that offers a variety of activities for visitors to enjoy. The park has a playground, a picnic area, a walking trail, and a pond.

Jackson, Georgia area median rent change by ZIP Code map

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How does Jackson compare to other cities in Georgia ?

citymedian price
Columbus$975
Loganville$2,055
Adairsville$1,930
Rockmart$1,649
Hampton$1,915
Snellville$1,915
Rex$1,725
Hephzibah$1,105

Average household income in Jackson area graph - US Census

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The median household income in Jackson in 2021 was $41,498. This represents a 23.2% change from 2011 when the median was $33,693.

#categorypercent
0Less than $10,0005.4%
1$10,000 to $14,9999.1%
2$15,000 to $19,9990.5%
3$20,000 to $24,9998.3%
4$25,000 to $29,9996.2%
5$30,000 to $34,9994.1%
6$35,000 to $39,99910.6%
7$40,000 to $44,99917.0%
8$45,000 to $49,9998.4%
9$50,000 to $59,9990.9%
10$60,000 to $74,9996.7%
11$75,000 to $99,9996.7%
12$100,000 to $124,9996.5%
13$125,000 to $149,9994.1%
14$150,000 to $199,9991.7%
15$200,000 or more3.9%

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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