Install Data2Sales AI
Faster access, offline browsing, and a one-tap shortcut on your home screen.
This dataset covers 1,847 verified records spread across 254+ districts in Texas. 1,847 records carry a verified phone number and 646 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Brown (302 listings), Dallas (151 listings), San Patricio (101 listings), Grayson (75 listings), Stephens (60 listings), Washington (50 listings), Colorado (43 listings), and Collin (38 listings).
Additional coverage spans McCulloch (34), Nacogdoches (30), Williamson (27), Burnet (25), Henderson (23), Travis (22), Kleberg (20), Van Zandt (19), Wharton (18), Wise (17), Shackelford (16), Lubbock (15) , plus 234 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Brown | 302 | 302 | 106 |
| Dallas | 151 | 151 | 53 |
| San Patricio | 101 | 101 | 35 |
| Grayson | 75 | 75 | 26 |
| Stephens | 60 | 60 | 21 |
| Washington | 50 | 50 | 18 |
| Colorado | 43 | 43 | 15 |
| Collin | 38 | 38 | 13 |
| McCulloch | 34 | 34 | 12 |
| Nacogdoches | 30 | 30 | 11 |
| All districts (254) | 1,847 | 1,847 | 646 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Brown | 302 | 302 | 106 |
| Dallas | 151 | 151 | 53 |
| San Patricio | 101 | 101 | 35 |
| Grayson | 75 | 75 | 26 |
| Stephens | 60 | 60 | 21 |
| Washington | 50 | 50 | 18 |
| Colorado | 43 | 43 | 15 |
| Collin | 38 | 38 | 13 |
| McCulloch | 34 | 34 | 12 |
| Nacogdoches | 30 | 30 | 11 |
| Williamson | 27 | 27 | 9 |
| Burnet | 25 | 25 | 9 |
| Henderson | 23 | 23 | 8 |
| Travis | 22 | 22 | 8 |
| Kleberg | 20 | 20 | 7 |
| Van Zandt | 19 | 19 | 7 |
| Wharton | 18 | 18 | 6 |
| Wise | 17 | 17 | 6 |
| Shackelford | 16 | 16 | 6 |
| Lubbock | 15 | 15 | 5 |
| Jack | 14 | 14 | 5 |
| Harris | 14 | 14 | 5 |
| Lavaca | 13 | 13 | 5 |
| Starr | 13 | 13 | 5 |
| San Saba | 12 | 12 | 4 |
| Brooks | 12 | 12 | 4 |
| Hays | 11 | 11 | 4 |
| Johnson | 11 | 11 | 4 |
| Orange | 10 | 10 | 4 |
| Liberty | 10 | 10 | 4 |
| King | 10 | 10 | 4 |
| Roberts | 9 | 9 | 3 |
| Kendall | 9 | 9 | 3 |
| Franklin | 9 | 9 | 3 |
| Coleman | 9 | 9 | 3 |
| Yoakum | 8 | 8 | 3 |
| Cherokee | 8 | 8 | 3 |
| Nueces | 8 | 8 | 3 |
| Hutchinson | 8 | 8 | 3 |
| Karnes | 8 | 8 | 3 |
| La Salle | 8 | 8 | 3 |
| Freestone | 7 | 7 | 2 |
| Reeves | 7 | 7 | 2 |
| Comanche | 7 | 7 | 2 |
| Titus | 7 | 7 | 2 |
| Tom Green | 7 | 7 | 2 |
| Real | 7 | 7 | 2 |
| Martin | 6 | 6 | 2 |
| Lipscomb | 6 | 6 | 2 |
| Gonzales | 6 | 6 | 2 |
| Galveston | 6 | 6 | 2 |
| Cass | 6 | 6 | 2 |
| Kimble | 6 | 6 | 2 |
| Runnels | 6 | 6 | 2 |
| Jasper | 6 | 6 | 2 |
| Ochiltree | 5 | 5 | 2 |
| Atascosa | 5 | 5 | 2 |
| Gray | 5 | 5 | 2 |
| Brazoria | 5 | 5 | 2 |
| Parmer | 5 | 5 | 2 |
| Crane | 5 | 5 | 2 |
| Floyd | 5 | 5 | 2 |
| Archer | 5 | 5 | 2 |
| Newton | 5 | 5 | 2 |
| Mitchell | 5 | 5 | 2 |
| Kenedy | 5 | 5 | 2 |
| Parker | 5 | 5 | 2 |
| Burleson | 5 | 5 | 2 |
| Pecos | 4 | 4 | 1 |
| Guadalupe | 4 | 4 | 1 |
| Cochran | 4 | 4 | 1 |
| Young | 4 | 4 | 1 |
| Carson | 4 | 4 | 1 |
| Zavala | 4 | 4 | 1 |
| Randall | 4 | 4 | 1 |
| Schleicher | 4 | 4 | 1 |
| Presidio | 4 | 4 | 1 |
| Coke | 4 | 4 | 1 |
| Haskell | 4 | 4 | 1 |
| Fannin | 4 | 4 | 1 |
| Caldwell | 4 | 4 | 1 |
| Aransas | 4 | 4 | 1 |
| Fayette | 4 | 4 | 1 |
| Jeff Davis | 4 | 4 | 1 |
| Kaufman | 4 | 4 | 1 |
| Chambers | 4 | 4 | 1 |
| Tyler | 4 | 4 | 1 |
| Victoria | 3 | 3 | 1 |
| Mason | 3 | 3 | 1 |
| Baylor | 3 | 3 | 1 |
| Callahan | 3 | 3 | 1 |
| Robertson | 3 | 3 | 1 |
| Jefferson | 3 | 3 | 1 |
| Wilson | 3 | 3 | 1 |
| Fisher | 3 | 3 | 1 |
| Uvalde | 3 | 3 | 1 |
| Swisher | 3 | 3 | 1 |
| Hardin | 3 | 3 | 1 |
| Cottle | 3 | 3 | 1 |
| Collingsworth | 3 | 3 | 1 |
| Medina | 3 | 3 | 1 |
| Bailey | 3 | 3 | 1 |
| Terrell | 3 | 3 | 1 |
| Jackson | 3 | 3 | 1 |
| Hidalgo | 3 | 3 | 1 |
| Wilbarger | 3 | 3 | 1 |
| Brewster | 3 | 3 | 1 |
| Marion | 3 | 3 | 1 |
| Dawson | 3 | 3 | 1 |
| Comal | 3 | 3 | 1 |
| Angelina | 3 | 3 | 1 |
| Castro | 3 | 3 | 1 |
| Live Oak | 3 | 3 | 1 |
| Austin | 3 | 3 | 1 |
| Ward | 3 | 3 | 1 |
| Fort Bend | 3 | 3 | 1 |
| Panola | 3 | 3 | 1 |
| Nolan | 3 | 3 | 1 |
| San Jacinto | 3 | 3 | 1 |
| Erath | 3 | 3 | 1 |
| Stonewall | 3 | 3 | 1 |
| Red River | 2 | 2 | 1 |
| Camp | 2 | 2 | 1 |
| DeWitt | 2 | 2 | 1 |
| Hamilton | 2 | 2 | 1 |
| Falls | 2 | 2 | 1 |
| Wood | 2 | 2 | 1 |
| Milam | 2 | 2 | 1 |
| Bandera | 2 | 2 | 1 |
| Hardeman | 2 | 2 | 1 |
| Briscoe | 2 | 2 | 1 |
| Brazos | 2 | 2 | 1 |
| Gillespie | 2 | 2 | 1 |
| Hopkins | 2 | 2 | 1 |
| San Augustine | 2 | 2 | 1 |
| Midland | 2 | 2 | 1 |
| Jones | 2 | 2 | 1 |
| Hood | 2 | 2 | 1 |
| Motley | 2 | 2 | 1 |
| Sabine | 2 | 2 | 1 |
| Winkler | 2 | 2 | 1 |
| Taylor | 2 | 2 | 1 |
| McLennan | 2 | 2 | 1 |
| Knox | 2 | 2 | 1 |
| Donley | 2 | 2 | 1 |
| Menard | 2 | 2 | 1 |
| Kent | 2 | 2 | 1 |
| Palo Pinto | 2 | 2 | 1 |
| Trinity | 2 | 2 | 1 |
| Smith | 2 | 2 | 1 |
| Walker | 2 | 2 | 1 |
| Waller | 2 | 2 | 1 |
| Sherman | 2 | 2 | 1 |
| El Paso | 2 | 2 | 1 |
| Jim Wells | 2 | 2 | 1 |
| Hunt | 2 | 2 | 1 |
| Lampasas | 2 | 2 | 1 |
| Kerr | 2 | 2 | 1 |
| Throckmorton | 2 | 2 | 1 |
| Childress | 2 | 2 | 1 |
| Clay | 2 | 2 | 1 |
| Willacy | 2 | 2 | 1 |
| Hockley | 2 | 2 | 1 |
| Shelby | 2 | 2 | 1 |
| Bee | 2 | 2 | 1 |
| Howard | 2 | 2 | 1 |
| Hall | 2 | 2 | 1 |
| Crockett | 2 | 2 | 1 |
| Eastland | 2 | 2 | 1 |
| Hudspeth | 2 | 2 | 1 |
| Polk | 2 | 2 | 1 |
| Hill | 2 | 2 | 1 |
| Harrison | 2 | 2 | 1 |
| Oldham | 2 | 2 | 1 |
| Cameron | 2 | 2 | 1 |
| Limestone | 2 | 2 | 1 |
| Lee | 2 | 2 | 1 |
| Bosque | 2 | 2 | 1 |
| Denton | 2 | 2 | 1 |
| Culberson | 2 | 2 | 1 |
| Hansford | 2 | 2 | 1 |
| Coryell | 2 | 2 | 1 |
| Montague | 2 | 2 | 1 |
| Potter | 2 | 2 | 1 |
| Val Verde | 2 | 2 | 1 |
| Houston | 2 | 2 | 1 |
| Wichita | 2 | 2 | 1 |
| Ellis | 2 | 2 | 1 |
| Dickens | 2 | 2 | 1 |
| Hemphill | 2 | 2 | 1 |
| Madison | 2 | 2 | 1 |
| Edwards | 2 | 2 | 1 |
| Garza | 2 | 2 | 1 |
| Goliad | 2 | 2 | 1 |
| Frio | 2 | 2 | 1 |
| Reagan | 2 | 2 | 1 |
| Deaf Smith | 2 | 2 | 1 |
| Montgomery | 2 | 2 | 1 |
| Foard | 2 | 2 | 1 |
| Anderson | 2 | 2 | 1 |
| Upshur | 2 | 2 | 1 |
| Concho | 2 | 2 | 1 |
| Bastrop | 1 | 1 | 0 |
| Calhoun | 1 | 1 | 0 |
| Terry | 1 | 1 | 0 |
| Moore | 1 | 1 | 0 |
| Somervell | 1 | 1 | 0 |
| Hartley | 1 | 1 | 0 |
| Mills | 1 | 1 | 0 |
| Bell | 1 | 1 | 0 |
| Borden | 1 | 1 | 0 |
| Webb | 1 | 1 | 0 |
| Wheeler | 1 | 1 | 0 |
| Rusk | 1 | 1 | 0 |
| Armstrong | 1 | 1 | 0 |
| Jim Hogg | 1 | 1 | 0 |
| Gaines | 1 | 1 | 0 |
| Lamb | 1 | 1 | 0 |
| Tarrant | 1 | 1 | 0 |
| Rockwall | 1 | 1 | 0 |
| Bexar | 1 | 1 | 0 |
| Ector | 1 | 1 | 0 |
| Navarro | 1 | 1 | 0 |
| Scurry | 1 | 1 | 0 |
| Rains | 1 | 1 | 0 |
| Dimmit | 1 | 1 | 0 |
| Hale | 1 | 1 | 0 |
| Maverick | 1 | 1 | 0 |
| Sterling | 1 | 1 | 0 |
| Lynn | 1 | 1 | 0 |
| Glasscock | 1 | 1 | 0 |
| Llano | 1 | 1 | 0 |
| Refugio | 1 | 1 | 0 |
| Upton | 1 | 1 | 0 |
| Leon | 1 | 1 | 0 |
| McMullen | 1 | 1 | 0 |
| Kinney | 1 | 1 | 0 |
| Cooke | 1 | 1 | 0 |
| Zapata | 1 | 1 | 0 |
| Irion | 1 | 1 | 0 |
| Sutton | 1 | 1 | 0 |
| Andrews | 1 | 1 | 0 |
| Grimes | 1 | 1 | 0 |
| Duval | 1 | 1 | 0 |
| Bowie | 1 | 1 | 0 |
| Crosby | 1 | 1 | 0 |
| Gregg | 1 | 1 | 0 |
| Morris | 1 | 1 | 0 |
| Lamar | 1 | 1 | 0 |
| Loving | 1 | 1 | 0 |
| Matagorda | 1 | 1 | 0 |
| Blanco | 1 | 1 | 0 |
| Dallam | 1 | 1 | 0 |
| Delta | 1 | 1 | 0 |
| All districts (254) | 1,847 | 1,847 | 646 |
The Shoe stores database includes 1,847+ verified Shoe stores in Texas, United States with name, address, city, state, phone, hours, website and GPS coordinates. The file is delivered as a CSV ready for CRM import or BI analysis.
Reyes (IN) bought 1 hour ago · Joel (US) bought 1 day ago · Scott (US) bought 3 days ago · Tanya (US) bought 4 days ago · Daren (IN) bought 5 days ago
Counting only operational sites, the Shoe footprint in Texas, United States sits at about 1,847+ stores this 2026. The CSV on this page covers all of them — phones, hours, GPS, the lot.
This page IS the download point. The Shoe stores CSV for Texas, United States ships immediately after payment and includes all verified store-level fields.
Each Shoe record carries the full operational profile: Shoe store name, Street address, City, State / Region, Postal code, Country, Phone number, Website URL along with website, hours, Google rating and review volume. CSV opens directly in Excel / Sheets / Power BI / Looker.
We verify each Shoe entry against the brand's official locator, Google Places and our directory partners on a 30-day cycle. Anything closed or with a dead phone gets dropped before export, so the CSV is the live Texas, United States footprint, not last year's.
Yes. The Shoe stores dataset is rebuilt on a rolling 30-day cycle — new openings come in through franchise expansion feeds and registrar filings, closures are detected from negative Google signals (phone disconnected, 'permanently closed' markers) and dropped before export.
Yes — the dataset is licensed for commercial use after purchase. Common use cases include geo-targeted advertising against Shoe catchments, competitor benchmarking, site-selection analytics, supplier outreach and franchise planning. Personal consumer data is not included, only publicly listed business contact information.
You receive a UTF-8 encoded CSV file. It opens cleanly in Excel, Google Sheets, Power BI, Looker Studio and every major CRM (HubSpot, Salesforce, Zoho, Pipedrive). XLSX is available on request after purchase.
Within 30 seconds of successful payment. The CSV is generated fresh from the live database at purchase time, so you always receive the latest verified Shoe stores — not a stale snapshot. You also get 7 days of unlimited re-downloads from a secure link sent to your email.
Looking to reach world wide data decision-makers in Texas, United States? This database aggregates 1,847+ verified records through the Data2Sales AI engine, pulling from verified public registries, official websites, social profiles, and licensed data partners. Dead numbers, closed storefronts, and duplicates are stripped before export — you receive a clean, CRM-ready CSV.
Buy multiple neighbouring states in a single file. Cheaper than the country pack, wider than any one state.
Last Update:
Aug 07, 2026 02:32 AM
Published:
May 11, 2026 04:16 AM
Rows (Regular):
924
Rows (Extended):
1,847
Category:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
