Starbucks
U.S. · 15,185 locations
Starbucks operates 15,180 locations across 49 US states. This dataset contains verified Starbucks store locations with street address, phone, and GPS coordinates — deduplicated by 50-meter spheroid distance from multi-source public POI data.
More about this list
Used by competitive retailers measuring market overlap, commercial real estate analysts benchmarking footprints, franchise consultants mapping territory density, and distribution planners identifying white space.
The file has all 15,185 locations across 49 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 | county note | address quality | country | latitude | longitude |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Starbucks | 250 S Colonial Dr | Alabaster | AL | 35007-4657 | (205) 564-2608 | https://www.starbucks.com/store-locator/store/12594 | source | Shelby County | 01117 | complete | US | 33.224555 | -86.804203 | |
| Starbucks | 3622 N Cobb Pkwy NW | Acworth | GA | 30101-4018 | (770) 966-9262 | https://www.starbucks.com/store-locator/store/17280/ | source | Cobb County | 13067 | complete | US | 34.044456 | -84.695591 | |
| Starbucks | 35 Mt Auburn Ave | Auburn | ME | 04210-8521 | (207) 782-0674 | https://www.starbucks.com/store-locator/store/9598/ | source | Androscoggin County | 23001 | complete | US | 44.12058 | -70.234304 | |
| Starbucks | 1109 RT-34 | Aberdeen Twp | NJ | 07747-2166 | (732) 395-8381 | https://www.starbucks.com/store-locator/store/1019311 | source | Monmouth County | 34025 | complete | US | 40.398068 | -74.226015 | |
| Starbucks | 3307 7th Ave SE | Aberdeen | SD | 57401-6613 | (605) 225-0226 | https://www.starbucks.com/store-locator/store/1007745/ | source | Brown County | 46013 | complete | US | 45.458726 | -98.441921 |
{}What's in each row
| Field | What it is | Rows filled |
|---|---|---|
| name | Store name and number | 100% |
| address | Street address | 100% |
| city | City name | 100% |
| state | Two-letter state code | 100% |
| zip | 5-digit ZIP code | 100% |
| country | Country code (US) | 100% |
| phone | Store phone number | 96% |
| latitude | GPS latitude coordinate | 100% |
| longitude | GPS longitude coordinate | 100% |
| url | Url | 99% |
| 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% |
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 Starbucks's store network across the US, deduplicated by 50-meter distance to one record per physical store.
September 14, 2026
File built
15 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 Starbucks Locations and give it this page: it can open https://locationlists.com/find?dataset=starbucks-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 California, the state with the most: https://locationlists.com/find?dataset=starbucks-stores&state=CA
- Within 25 miles of Los Angeles, CA, the busiest area: https://locationlists.com/find?dataset=starbucks-stores&near=Los+Angeles+CA&radius=25
- Within a 30-minute drive of Los Angeles, CA: https://locationlists.com/find?dataset=starbucks-stores&near=Los+Angeles+CA&drive=30
- Every Quick Service & Fast Casual list combined, within 25 miles of Huntington Park, CA: https://locationlists.com/find?category=quick-service-restaurant&near=Huntington+Park+CA&radius=25
- Each one's nearest McDonald's Locations, in California, with miles: https://locationlists.com/find?dataset=starbucks-stores&state=CA&relate=nearest&k=1&b.dataset=mcdonalds-stores&b.state=CA
- The whole list: add a city, state, ZIP code or distance:
https://locationlists.com/find?dataset=starbucks-stores - In plain words: "Starbucks Locations in California": https://locationlists.com/find?q=Starbucks+Locations+in+California
- In plain words: "Starbucks Locations within 25 miles of Los Angeles, CA": https://locationlists.com/find?q=Starbucks+Locations+within+25+miles+of+Los+Angeles%2C+CA
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 Starbucks Locations list.Your assistant will walk you through setup and show you the price before you pay.
For developers
Every step below has a no-connector equivalent: https://locationlists.com/find?dataset=starbucks-stores with the same filters as query parameters.
- Connect your agent to
https://locationlists.com/mcp(no key, no signup). - Call
count_locationswithdataset: "starbucks-stores"and any filter — it is free, and returns how many rows match and what they cost. - Fetch the rows with
query_locations: $0.92 per 100 rows from this dataset. Above 7,593 rows, buying the whole file is cheaper.
Paid in USDC over x402 — the agent gets an HTTP 402 with the exact price, signs, and retries. Money moves only after rows are delivered, so a failed or empty query costs nothing. Setup for Claude, Cursor and VS Code
?Frequently Asked Questions
How many Starbucks locations are in this dataset?
15,180 deduplicated store locations across 49 US states.
What fields are in the CSV?
Name, street address, city, state, ZIP, phone, latitude/longitude, and website URL. Standard CSV ready for any CRM, GIS tool, or spreadsheet.
How is Starbucks data compiled?
We aggregate from multiple public POI sources and apply a 50-meter spheroid-distance deduplication pass to produce one verified record per physical location. Cross-checked against published Starbucks store counts.
How often is the dataset updated?
File built on September 14, 2026. It is not on an automatic refresh schedule, so check the build date above before you buy.
How do we use Starbucks location data for competitive analysis?
Mapping Starbucks's 15,325-location footprint by state and metro lets you benchmark your coverage, identify white space, and quantify overlap with competing chains. The GPS coordinates enable catchment, trade-area, and drive-time analysis against census and demographic data.