Rent-A-Center
U.S. Location Dataset // 1,962
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. 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.
●Coverage Map
Rent-A-Center dealer locations in the USA
1,962 locations · Source: LocationLists.com
☆Who uses this data
Sales & Business Development
Territory planning, lead generation, and prospecting for teams selling products or services to stores
Market Research & Competitive Intelligence
Analyzing Rent-A-Center's geographic footprint, density, and overlap with competitors
Logistics & Supply Chain
Route optimization, delivery planning, and distribution network analysis across 1,962 locations
Real Estate & Site Selection
Co-tenancy analysis, trade area studies, and identifying expansion opportunities near existing stores
✓Data quality & methodology
This dataset is compiled from multi-source public geographic POI data covering Rent-A-Center's store network across the US. Each record is cross-referenced across upstream sources and deduplicated by 50-meter spheroid distance to produce one verified record per physical store.
Monthly
Refresh frequency
Deduplicated
By 50m proximity
Validated
Format checks on all fields
Every record goes through automated quality checks including ZIP code format validation, coordinate bounds verification (US only), phone number standardization, and duplicate detection. Records that fail validation are flagged and excluded from the dataset.
Location data aggregated from public geographic sources including © Overture Maps Foundation contributors.
{}Data Fields
≡Sample Data Preview
| name | address | city | state | zip | country | phone | latitude |
|---|---|---|---|---|---|---|---|
| Rent-A-Center | Ashland | KY | US | +16063249306 | 38.477049 | ||
| Rent-A-Center | 125 S 24th St W | Billings | MT | 59102-5606 | US | +14066562078 | 45.765061 |
| Rent-A-Center | 710 NW MO-7 | Blue Springs | MO | 64014-2425 | US | +18162281224 | 39.025681 |
| Rent-A-Center | 816 N White Sands Blvd | Alamogordo | NM | 88310-7112 | US | +15754372200 | 32.898302 |
| Rent-A-Center | 2480 S Santa Fe Ave | Chanute | KS | 66720-3202 | US | +16204312000 | 37.656322 |
Rent-A-Center Locations
1,962 locations · CSV · Updated monthly
?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 1,962 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.