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This dataset covers 8,605 verified records spread across 254+ districts in Texas. 8,605 records carry a verified phone number and 3,012 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Hemphill (1,407 listings), Grimes (703 listings), Sutton (469 listings), Loving (352 listings), Morris (281 listings), Crosby (234 listings), Dallam (201 listings), and Blanco (176 listings).
Additional coverage spans Glasscock (156), Montague (141), Hansford (128), Falls (117), Nolan (108), Erath (100), Harrison (94), Hays (88), King (83), Lee (78), Hidalgo (74), Williamson (70) , plus 234 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Hemphill | 1,407 | 1,407 | 492 |
| Grimes | 703 | 703 | 246 |
| Sutton | 469 | 469 | 164 |
| Loving | 352 | 352 | 123 |
| Morris | 281 | 281 | 98 |
| Crosby | 234 | 234 | 82 |
| Dallam | 201 | 201 | 70 |
| Blanco | 176 | 176 | 62 |
| Glasscock | 156 | 156 | 55 |
| Montague | 141 | 141 | 49 |
| All districts (254) | 8,605 | 8,605 | 3,012 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Hemphill | 1,407 | 1,407 | 492 |
| Grimes | 703 | 703 | 246 |
| Sutton | 469 | 469 | 164 |
| Loving | 352 | 352 | 123 |
| Morris | 281 | 281 | 98 |
| Crosby | 234 | 234 | 82 |
| Dallam | 201 | 201 | 70 |
| Blanco | 176 | 176 | 62 |
| Glasscock | 156 | 156 | 55 |
| Montague | 141 | 141 | 49 |
| Hansford | 128 | 128 | 45 |
| Falls | 117 | 117 | 41 |
| Nolan | 108 | 108 | 38 |
| Erath | 100 | 100 | 35 |
| Harrison | 94 | 94 | 33 |
| Hays | 88 | 88 | 31 |
| King | 83 | 83 | 29 |
| Lee | 78 | 78 | 27 |
| Hidalgo | 74 | 74 | 26 |
| Williamson | 70 | 70 | 25 |
| Jack | 67 | 67 | 23 |
| Jackson | 64 | 64 | 22 |
| Terrell | 61 | 61 | 21 |
| Wise | 59 | 59 | 21 |
| Washington | 56 | 56 | 20 |
| Comal | 54 | 54 | 19 |
| Matagorda | 52 | 52 | 18 |
| Zapata | 50 | 50 | 18 |
| Eastland | 49 | 49 | 17 |
| Swisher | 47 | 47 | 16 |
| Bee | 45 | 45 | 16 |
| Hudspeth | 44 | 44 | 15 |
| Kinney | 43 | 43 | 15 |
| Crockett | 41 | 41 | 14 |
| Tyler | 40 | 40 | 14 |
| Mason | 39 | 39 | 14 |
| Borden | 38 | 38 | 13 |
| Lampasas | 37 | 37 | 13 |
| Gaines | 36 | 36 | 13 |
| Real | 35 | 35 | 12 |
| Somervell | 34 | 34 | 12 |
| Kaufman | 33 | 33 | 12 |
| Dimmit | 33 | 33 | 12 |
| San Augustine | 32 | 32 | 11 |
| Scurry | 31 | 31 | 11 |
| Fayette | 31 | 31 | 11 |
| Aransas | 30 | 30 | 11 |
| Upshur | 29 | 29 | 10 |
| Armstrong | 29 | 29 | 10 |
| Haskell | 28 | 28 | 10 |
| Young | 28 | 28 | 10 |
| McLennan | 27 | 27 | 9 |
| Hutchinson | 27 | 27 | 9 |
| Concho | 26 | 26 | 9 |
| Gray | 26 | 26 | 9 |
| Randall | 25 | 25 | 9 |
| Cochran | 25 | 25 | 9 |
| Cass | 24 | 24 | 8 |
| Hardeman | 24 | 24 | 8 |
| Potter | 23 | 23 | 8 |
| Coke | 23 | 23 | 8 |
| Jeff Davis | 23 | 23 | 8 |
| Denton | 22 | 22 | 8 |
| La Salle | 22 | 22 | 8 |
| Pecos | 22 | 22 | 8 |
| Runnels | 21 | 21 | 7 |
| Limestone | 21 | 21 | 7 |
| Reagan | 21 | 21 | 7 |
| Goliad | 20 | 20 | 7 |
| Floyd | 20 | 20 | 7 |
| Crane | 20 | 20 | 7 |
| Val Verde | 20 | 20 | 7 |
| McMullen | 19 | 19 | 7 |
| Culberson | 19 | 19 | 7 |
| Shelby | 19 | 19 | 7 |
| Howard | 19 | 19 | 7 |
| Schleicher | 18 | 18 | 6 |
| Oldham | 18 | 18 | 6 |
| San Patricio | 18 | 18 | 6 |
| Maverick | 18 | 18 | 6 |
| Bosque | 17 | 17 | 6 |
| Sterling | 17 | 17 | 6 |
| Titus | 17 | 17 | 6 |
| Coleman | 17 | 17 | 6 |
| Kendall | 17 | 17 | 6 |
| Roberts | 16 | 16 | 6 |
| Walker | 16 | 16 | 6 |
| Menard | 16 | 16 | 6 |
| Liberty | 16 | 16 | 6 |
| Johnson | 16 | 16 | 6 |
| Donley | 15 | 15 | 5 |
| Rockwall | 15 | 15 | 5 |
| Gillespie | 15 | 15 | 5 |
| Waller | 15 | 15 | 5 |
| Lubbock | 15 | 15 | 5 |
| Wharton | 15 | 15 | 5 |
| Jim Hogg | 15 | 15 | 5 |
| Kleberg | 14 | 14 | 5 |
| Starr | 14 | 14 | 5 |
| Camp | 14 | 14 | 5 |
| Brown | 14 | 14 | 5 |
| Brazos | 14 | 14 | 5 |
| Sabine | 14 | 14 | 5 |
| Ward | 14 | 14 | 5 |
| Jim Wells | 13 | 13 | 5 |
| Anderson | 13 | 13 | 5 |
| Motley | 13 | 13 | 5 |
| Grayson | 13 | 13 | 5 |
| Childress | 13 | 13 | 5 |
| Taylor | 13 | 13 | 5 |
| Brazoria | 13 | 13 | 5 |
| Palo Pinto | 13 | 13 | 5 |
| Castro | 12 | 12 | 4 |
| Lamar | 12 | 12 | 4 |
| Gregg | 12 | 12 | 4 |
| Knox | 12 | 12 | 4 |
| Hood | 12 | 12 | 4 |
| Panola | 12 | 12 | 4 |
| Mitchell | 12 | 12 | 4 |
| Irion | 12 | 12 | 4 |
| Austin | 12 | 12 | 4 |
| Bowie | 12 | 12 | 4 |
| Duval | 11 | 11 | 4 |
| Burleson | 11 | 11 | 4 |
| Wilbarger | 11 | 11 | 4 |
| Wood | 11 | 11 | 4 |
| Andrews | 11 | 11 | 4 |
| Atascosa | 11 | 11 | 4 |
| DeWitt | 11 | 11 | 4 |
| Delta | 11 | 11 | 4 |
| Kerr | 11 | 11 | 4 |
| Comanche | 11 | 11 | 4 |
| Hunt | 11 | 11 | 4 |
| Hardin | 10 | 10 | 4 |
| Fisher | 10 | 10 | 4 |
| Uvalde | 10 | 10 | 4 |
| Refugio | 10 | 10 | 4 |
| Bailey | 10 | 10 | 4 |
| Lipscomb | 10 | 10 | 4 |
| Medina | 10 | 10 | 4 |
| Gonzales | 10 | 10 | 4 |
| Fort Bend | 10 | 10 | 4 |
| Cottle | 10 | 10 | 4 |
| Franklin | 10 | 10 | 4 |
| Stonewall | 10 | 10 | 4 |
| Red River | 10 | 10 | 4 |
| Cooke | 10 | 10 | 4 |
| Cherokee | 10 | 10 | 4 |
| Llano | 9 | 9 | 3 |
| Upton | 9 | 9 | 3 |
| Dawson | 9 | 9 | 3 |
| Kent | 9 | 9 | 3 |
| Marion | 9 | 9 | 3 |
| Navarro | 9 | 9 | 3 |
| San Saba | 9 | 9 | 3 |
| Guadalupe | 9 | 9 | 3 |
| Tarrant | 9 | 9 | 3 |
| Hill | 9 | 9 | 3 |
| Ector | 9 | 9 | 3 |
| Bexar | 9 | 9 | 3 |
| Rains | 9 | 9 | 3 |
| Shackelford | 9 | 9 | 3 |
| Polk | 9 | 9 | 3 |
| Baylor | 9 | 9 | 3 |
| Hall | 9 | 9 | 3 |
| Clay | 8 | 8 | 3 |
| Montgomery | 8 | 8 | 3 |
| Wilson | 8 | 8 | 3 |
| Wheeler | 8 | 8 | 3 |
| Deaf Smith | 8 | 8 | 3 |
| Colorado | 8 | 8 | 3 |
| Frio | 8 | 8 | 3 |
| Carson | 8 | 8 | 3 |
| Foard | 8 | 8 | 3 |
| Hartley | 8 | 8 | 3 |
| Nacogdoches | 8 | 8 | 3 |
| Calhoun | 8 | 8 | 3 |
| Bastrop | 8 | 8 | 3 |
| Mills | 8 | 8 | 3 |
| Stephens | 8 | 8 | 3 |
| Zavala | 8 | 8 | 3 |
| Jefferson | 8 | 8 | 3 |
| Fannin | 8 | 8 | 3 |
| Terry | 8 | 8 | 3 |
| Moore | 8 | 8 | 3 |
| Robertson | 8 | 8 | 3 |
| Kimble | 8 | 8 | 3 |
| Ellis | 7 | 7 | 2 |
| Bell | 7 | 7 | 2 |
| Throckmorton | 7 | 7 | 2 |
| Edwards | 7 | 7 | 2 |
| Madison | 7 | 7 | 2 |
| Dickens | 7 | 7 | 2 |
| San Jacinto | 7 | 7 | 2 |
| Jasper | 7 | 7 | 2 |
| Hamilton | 7 | 7 | 2 |
| Wichita | 7 | 7 | 2 |
| Archer | 7 | 7 | 2 |
| Parmer | 7 | 7 | 2 |
| Freestone | 7 | 7 | 2 |
| Houston | 7 | 7 | 2 |
| Tom Green | 7 | 7 | 2 |
| Live Oak | 7 | 7 | 2 |
| Parker | 7 | 7 | 2 |
| Coryell | 7 | 7 | 2 |
| Garza | 7 | 7 | 2 |
| Newton | 7 | 7 | 2 |
| Kenedy | 7 | 7 | 2 |
| Collingsworth | 7 | 7 | 2 |
| Yoakum | 7 | 7 | 2 |
| Hale | 7 | 7 | 2 |
| Galveston | 7 | 7 | 2 |
| Cameron | 7 | 7 | 2 |
| Ochiltree | 7 | 7 | 2 |
| Karnes | 7 | 7 | 2 |
| Brewster | 7 | 7 | 2 |
| Nueces | 6 | 6 | 2 |
| Angelina | 6 | 6 | 2 |
| Lamb | 6 | 6 | 2 |
| Hockley | 6 | 6 | 2 |
| Reeves | 6 | 6 | 2 |
| Rusk | 6 | 6 | 2 |
| Martin | 6 | 6 | 2 |
| Willacy | 6 | 6 | 2 |
| Webb | 6 | 6 | 2 |
| Callahan | 6 | 6 | 2 |
| El Paso | 6 | 6 | 2 |
| Leon | 6 | 6 | 2 |
| Sherman | 6 | 6 | 2 |
| Smith | 6 | 6 | 2 |
| Brooks | 6 | 6 | 2 |
| Lavaca | 6 | 6 | 2 |
| Harris | 6 | 6 | 2 |
| Lynn | 6 | 6 | 2 |
| McCulloch | 6 | 6 | 2 |
| Chambers | 6 | 6 | 2 |
| Henderson | 6 | 6 | 2 |
| Trinity | 6 | 6 | 2 |
| Orange | 6 | 6 | 2 |
| Victoria | 6 | 6 | 2 |
| Presidio | 6 | 6 | 2 |
| Winkler | 6 | 6 | 2 |
| Dallas | 6 | 6 | 2 |
| Van Zandt | 6 | 6 | 2 |
| Milam | 6 | 6 | 2 |
| Caldwell | 6 | 6 | 2 |
| Midland | 6 | 6 | 2 |
| Hopkins | 6 | 6 | 2 |
| Burnet | 6 | 6 | 2 |
| Briscoe | 6 | 6 | 2 |
| Collin | 6 | 6 | 2 |
| Bandera | 6 | 6 | 2 |
| Travis | 6 | 6 | 2 |
| Jones | 3 | 3 | 1 |
| All districts (254) | 8,605 | 8,605 | 3,012 |
The Office Cleaning Services database for Texas, United States includes 8,605+ verified businesses with company name, address, city, state, phone, email, website and GPS coordinates. The file is delivered as a CSV ready for CRM import or BI analysis.
The Office Cleaning Services database for Texas, United States contains 8,605+ verified businesses as of 2026, each with phone, email, address, website and GPS coordinates. The full record count is shown on this page above.
The complete Office Cleaning Services database for Texas, United States is available on this page from Data2Sales AI as an instant CSV download. Every record carries verified contact details and is delivered immediately after checkout.
Each record includes: Business name, Street address, City, State / Region, Postal code, Country, Phone number, Email address and more. The file is delivered as a UTF-8 CSV that opens in Excel, Google Sheets or any standard CRM importer.
Every record is cross-referenced across public business registries, Google Maps and licensed directory partners before it ships. Closed businesses, disconnected phones and duplicates are stripped on every monthly refresh, so the dataset reflects the live office cleaning services footprint in Texas, United States.
Yes. The Office Cleaning Services dataset is rebuilt on a rolling 30-day cycle. New entrants come in through registrar filings; closures are detected from negative signals and dropped before export.
Yes — the dataset is licensed for commercial use after purchase. Common use cases include cold outbound, geo-targeted advertising, market research, supplier sourcing and territory planning. Only publicly listed business contact information is included.
You receive a UTF-8 encoded CSV. It opens in Excel, Google Sheets, Power BI, Looker Studio and every major CRM (HubSpot, Salesforce, Zoho, Pipedrive). XLSX is available on request.
Within 30 seconds of successful payment. The CSV is generated fresh from the live database at purchase time. 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 8,605+ 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:
Jul 08, 2026 13:38 PM
Published:
May 11, 2026 04:16 AM
Rows (Regular):
3,872
Rows (Extended):
8,605
Category:
Tags:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
