Rent-A-Center
U.S. · 1,956 locations
Rent-A-Center operates 1,962 rent-to-own storefronts across the U.S., making it the largest brick-and-mortar RTO chain by unit count — roughly 2x the footprint of its closest physical competitor, Aaron's, which has been aggressively closing stores since its 2020 PROG Holdings spinoff.
More about this list
Now a subsidiary of Upbound Group (rebranded 2023), Rent-A-Center's store network is deliberately concentrated in census tracts with above-average renter populations and below-median household incomes, functioning as a de facto credit channel for the ~45 million U.S. adults classified as credit-invisible or subprime. The stores skew heavily toward strip-mall inline placements rather than standalone pads, often co-tenanting with dollar stores, check-cashing outlets, and discount grocers — a clustering pattern that reveals trade-area demographics more reliably than zip-code-level proxies alone. This dataset is essential for consumer finance fintechs mapping underbanked population density, furniture and appliance manufacturers evaluating RTO wholesale channel potential, and commercial real estate analysts studying strip-mall tenant resilience in Class C retail corridors.
The file has all 1,956 locations across 46 states in one download. Building the same list by searching one area at a time tends to miss places, and a missed place looks like a gap in coverage that is not really there.
Need just some of them? Ask in your own words.
●Where the rows are
≡Sample Data Preview
| name | address | city | state | zip | phone | url | geo precision | county | county fips | address quality | county note | zip4 | country | latitude | longitude |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Rent-A-Center | 10999 AL-119 | Alabaster | AL | 35007 | (205) 664-1555 | https://locations.rentacenter.com/alabama/alabaster/11059-highway-119-s/ | source | Shelby County | 01117 | complete | 9701 | US | 33.238641 | -86.81718 | |
| Rent-A-Center | 222 Lincoln Way | Ames | IA | 50010 | (515) 233-6080 | https://locations.rentacenter.com/iowa/ames/222-lincoln-way/ | source | Story County | 19169 | complete | 3344 | US | 42.022543 | -93.613315 | |
| Rent-A-Center | 120 Center St | Auburn | ME | 04210 | (207) 782-8198 | https://locations.rentacenter.com/maine/auburn/120-center-street/ | source | Androscoggin County | 23001 | complete | 6000 | US | 44.105861 | -70.226955 | |
| Rent-A-Center | 1328 Atlantic Ave | Atlantic City | NJ | 08401 | (609) 344-4110 | https://locations.rentacenter.com/new-jersey/atlantic-city/1328-atlantic-ave/ | source | Atlantic County | 34001 | complete | 7208 | US | 39.361954 | -74.427501 | |
| Rent-A-Center | Aiken | SC | (803) 649-1305 | https://locations.rentacenter.com/south-carolina/aiken/1563-whiskey-rd-13/ | source | Aiken County | 45003 | missing | US | 33.5314 | -81.72468 |
{}What's in each row
| Field | What it is | Rows filled |
|---|---|---|
| name | Store name and number | 100% |
| address | Street address | 98% |
| city | City name | 100% |
| state | Two-letter state code | 100% |
| zip | 5-digit ZIP code | 98% |
| country | Country code (US) | 100% |
| phone | Store phone number | 99% |
| latitude | GPS latitude coordinate | 100% |
| longitude | GPS longitude coordinate | 100% |
| url | Url | 100% |
| geo_ | How exact the map point is: the source's own point, the street address, or the ZIP code's centre | 100% |
| county | County the location is in | 100% |
| county_ | Five-digit federal code of that county | 100% |
| address_ | Whether the street address is complete, missing a house number, or a PO box | 100% |
| county_ | How the county was found, where it was not given by the source | 29% |
| zip4 | Zip4 | 92% |
Rows filled is measured on every row of the delivered file.
✓Where this data comes from
This dataset is compiled from public geographic place data covering Rent-A-Center's store network across the US, deduplicated by 50-meter distance to one record per physical store.
September 20, 2026
File built
16 fields
Columns in the file
Fill measured
On every row of the delivered file
How we build and date every file: methodology.
Location data aggregated from public geographic sources including © Overture Maps Foundation contributors.
Using ChatGPT, Claude or an API?
No setup needed. Ask ChatGPT or Claude your question about the Rent-A-Center Locations and give it this page: it can open https://locationlists.com/find?dataset=rent-a-center-stores with the filters you need and show you the count and price.
Using ChatGPT or Claude? Tell it to answer from locationlists.com/find — no account, no connector.
How assistants ask
No connector needed. Any AI assistant can answer from this site with a web link, no connector, no account: open https://locationlists.com/find with the question as query parameters.
If a question needs filtering, distance, drive time, combining lists or a price, open a /find link: either put the question itself in q=, or build the structured link. The answer does not need an API, a connector or an account.
Simplest, the question itself: https://locationlists.com/find?q=<the question in plain words>
Or set the parts yourself: https://locationlists.com/find?dataset=<slug>&state=<ST>&city=<city>&county=<county>&zip=<zip>&near=<place or zip>&radius=<miles>&drive=<minutes>&where=<column>:<op>:<value>&total=<rows>
Leave out what the question does not need. Use radius for straight-line miles or drive for minutes of driving (5 to 60), not both; near can name several places separated by | to reach from any of them. To ask about several lists at once, use datasets with two or more names, or category with a kind of business. To compare two lists, add relate=nearest and the other list with b. in front of its parameters. To count by area, use areas=county (or zip, state, metro). To keep only places whose county, ZIP code, metro area or state meets a Census figure, add area_where (for example county:population>1000000); with areas, per=100000 gives counts per 100,000 residents.
Links an assistant can open, each showing how many rows match, a few preview rows and the price for just that part:
- Only Texas, the state with the most: https://locationlists.com/find?dataset=rent-a-center-stores&state=TX
- Within 25 miles of Dallas, TX, the busiest area: https://locationlists.com/find?dataset=rent-a-center-stores&near=Dallas+TX&radius=25
- Within a 30-minute drive of Dallas, TX: https://locationlists.com/find?dataset=rent-a-center-stores&near=Dallas+TX&drive=30
- Every Specialty Retail list combined, within 25 miles of Duncanville, TX: https://locationlists.com/find?category=specialty-retail&near=Duncanville+TX&radius=25
- Each one's nearest GameStop Locations, in Texas, with miles: https://locationlists.com/find?dataset=rent-a-center-stores&state=TX&relate=nearest&k=1&b.dataset=gamestop-stores&b.state=TX
- The whole list: add a city, state, ZIP code or distance:
https://locationlists.com/find?dataset=rent-a-center-stores - In plain words: "Rent-A-Center Locations in Texas": https://locationlists.com/find?q=Rent-A-Center+Locations+in+Texas
- In plain words: "Rent-A-Center Locations within 25 miles of Dallas, TX": https://locationlists.com/find?q=Rent-A-Center+Locations+within+25+miles+of+Dallas%2C+TX
Optional: connect for repeat use or wallet payments:
Read https://locationlists.com/skill.md and follow the instructions to connect LocationLists. Then show me the Rent-A-Center Locations list.Your assistant will walk you through setup and show you the price before you pay.
For developers
At 1,956 records this dataset is not sold by the row — buy the file. Without a connector, open https://locationlists.com/find?dataset=rent-a-center-stores. An agent connected to https://locationlists.com/mcp can still search it, read a free sample file of up to 10 rows and buy the whole file itself. How agent purchasing works
?Frequently Asked Questions
How does Rent-A-Center's 1,962-store footprint compare to Aaron's, and what does the gap mean for RTO market coverage analysis?
Rent-A-Center's network is roughly double the size of Aaron's remaining ~1,000 stores, a gap that widened significantly after Aaron's accelerated closures post-PROG Holdings spinoff. For anyone modeling RTO market coverage — say, a fintech building a virtual lease-to-own product — this dataset identifies the physical anchor points where RTO demand is already validated. If you need an overlay of both chains to find white-space or overlap markets, LocationLists can produce a custom co-location analysis.
I'm a furniture manufacturer evaluating rent-to-own as a wholesale channel. How can this data help me prioritize which Rent-A-Center regions to pitch first?
The dataset's geocoordinates let you cluster stores by DMA or state to quantify regional density — Texas, Florida, and the Southeast corridor typically have the highest concentrations, reflecting Rent-A-Center's historical expansion from its Plano, TX headquarters outward. Cross-referencing store density against your own distribution footprint identifies regions where logistics costs would be lowest. LocationLists can also run a territory optimization layer that ranks DMAs by store count per capita if you need a ready-to-present heat map.
Can this dataset help identify the demographic profile of Rent-A-Center trade areas without buying separate census data?
Indirectly, yes — and powerfully. Because Rent-A-Center's site-selection model is tightly calibrated to subprime and credit-thin populations, the geocoordinates in this dataset function as a proxy index for underbanked consumer density. Joining these 1,962 lat/long pairs to Census Bureau ACS block-group data (freely available) gives you a ready-made demographic profile of RTO-viable trade areas across the country.
I'm analyzing strip-mall tenant resilience for a CMBS portfolio. How does Rent-A-Center's store mix compare to co-tenants like Dollar General or CVS?
Rent-A-Center stores overwhelmingly occupy Class B/C strip centers rather than anchored power centers, making them a bellwether for the lower end of the inline retail market. LocationLists already catalogs CVS Pharmacy and several other national tenants; a custom overlap report can show you which shopping centers pair Rent-A-Center with specific co-tenants, giving you a co-tenancy risk or stability score per property. This is especially useful for identifying centers where multiple credit-sensitive tenants cluster.
Has Rent-A-Center's physical footprint been growing or shrinking, and does this dataset reflect the Acima virtual pivot?
Rent-A-Center's corporate store count has been gradually contracting — down from roughly 2,400 units a decade ago to the current 1,962 — as Upbound Group shifts growth investment toward Acima, its virtual lease-to-own platform embedded in third-party retailers. This dataset captures the physical storefront network only, which remains the profit engine for the traditional RTO segment. The contraction pattern itself is analytically valuable: comparing current locations to historical footprints reveals which trade areas Rent-A-Center deemed unviable.
We're a state consumer-protection agency studying rent-to-own concentration. Can we get this data broken down by state with store-per-capita ratios?
The raw dataset includes full state-level detail for all 1,956 locations, so generating per-capita ratios is straightforward once joined to state population tables. States like Texas, Alabama, and Mississippi typically show the highest RTO store density per 100,000 residents, which correlates with more permissive RTO regulatory frameworks. LocationLists can deliver a pre-processed state-level summary with density calculations as a custom deliverable if your team needs an analysis-ready format.