Apparel Manufacturer Locations

463 US apparel manufacturer businesses, from national chains to single independent shops, with address, phone, website and map coordinates.

$2.71for all 463 apparel manufacturer businesses, by card.

Buy the whole list — 463 rows · $2.71

Or ask for the part you need: an area, a distance, a condition. Counts and previews are free, and each answer shows its exact price.

Sample data

apparel-manufacturer-locations.csvscroll →UTF-8
nameaddresscitystatezipphonewebsiteoverture idbrandbrand idwikidatacategorycategory pathbasic categoryemailsocialoperating statusconfidencesource datasetsource record idsource idssource updateddata licenselocation typelocation type confidencelocation type basislatitudelongitude
Sole Search3147 DALEVIEW Way SWATLANTAGA30331(706) 395-8763http://www.solesearch.store/96ad50f6-03e5-4142-a694-9b5559e1949cshoe_factory_manufacturer|services_and_business|b2b_service|manufacturer|apparel_manufacturer|shoe_factory_manufacturer|manufactureropen0.92Microsoft844424933158380Microsoft:844424933158380|Overture-signals:bd0af46c-f004-41d0-821c-766a53b201362026-08-10Overture Maps Foundation, CDLA-Permissive-2.0plant0.43category: "manufacturer" (plant)33.669844-84.511482
Whitefish Printing & Apparel2006 68th St Unit DSomersetWI54025(651) 243-2246http://whitefishprinting.com/924d5469-4d41-49ed-97eb-50d968553977apparel_manufacturer|services_and_business|b2b_service|manufacturer|apparel_manufacturer|manufactureropen0.92Microsoft562949960192035Microsoft:562949960192035|Overture-signals:3482df9b-7816-4a0f-b3e9-9b6d237440e62026-08-10Overture Maps Foundation, CDLA-Permissive-2.0plant0.43category: "manufacturer" (plant)45.152561-92.676685
Dika Clothing201 Lakeview Dr Apt 203WestonFL33326(786) 397-9535https://linktr.ee/d1kaclothingc3408566-deba-4255-9a24-421c636366b6apparel_manufacturer|services_and_business|b2b_service|manufacturer|apparel_manufacturer|manufacturercontact@jcfashiongroup.comhttps://www.facebook.com/121077771881678open0.92meta121077771881678meta:121077771881678|Overture-signals:4d5d2d02-8cc9-4acc-8776-d1f80639caad2026-08-10Overture Maps Foundation, CDLA-Permissive-2.0plant0.43category: "manufacturer" (plant)26.129511-80.385906
Three sample rows; the file you buy has all 28 columns.

What's in each row

FieldWhat it is
overture_idMap data id for the place, stable across monthly releases
nameBusiness name
brandBrand or chain name, when the place belongs to one
brand_idOur id for that brand (its Wikidata id where one exists)
wikidataWikidata id of the brand
categoryKind of place, from the map data
category_pathThe category with every broader category above it
basic_categoryA broader, simpler category
addressStreet address
cityCity
stateState (two-letter code)
zipZIP code
phonePhone number
websiteWebsite
emailEmail address
socialSocial media page
latitudeLatitude
longitudeLongitude
operating_statusWhether the place is open, where the source says; closed places are left out of the list
confidenceHow sure the map data is that the place exists (0 to 1)
source_datasetWhich source contributed the record
source_record_idThe record's id in that source
source_idsEvery source record merged into this row
source_updatedWhen the source last updated the record
data_licenseThe license the row is published under
location_typeKind of premises: store, office, branch, warehouse and so on, read from the name, website and category
location_type_confidenceHow sure the location type is (0 to 1)
location_type_basisWhat the location type was read from

Source & license

Open map data from the Overture Maps Foundation, release of August 2026, refreshed monthly. Closed and low-confidence places are removed and duplicates within 50 meters merged. Contains data from Overture Maps Foundation (https://overturemaps.org), Places theme, licensed CDLA-Permissive-2.0 (https://cdla.dev/permissive-2-0/); some sources are Apache-2.0. See https://docs.overturemaps.org/attribution/.

Using ChatGPT, Claude or an API?

Ask this list a question with a link

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.

Open one of these to see how many places match, a few preview rows and the price for just those rows:

  • The whole list: add a city, state, ZIP code or distance: https://locationlists.com/find?dataset=apparel-manufacturer-locations

Ask in ChatGPT or Claude

Copy this and paste it in:

Using LocationLists, how many apparel manufacturer places are in Florida? Show a sample and the price.

Every answer shows its exact price before you pay, by card, no account; the whole list is $2.71. Counts, previews and comparisons with other lists are free.

For developers

Dataset slug apparel-manufacturer-locations. Machine-readable record: dataset.json. Without a connector, every one of these answers comes from a link: https://locationlists.com/find?dataset=apparel-manufacturer-locations. Works in every MCP tool and the x402 query API like any other dataset (count_locations, get_sample, query_locations, relate_locations, count_by_area, cotenancy).