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This dataset covers 2,385 verified records spread across 93+ districts in Indiana. 2,385 records carry a verified phone number and 835 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Rush (466 listings), Brown (233 listings), Bartholomew (155 listings), Vermillion (117 listings), Tippecanoe (93 listings), White (78 listings), Tipton (67 listings), and Sullivan (58 listings).
Additional coverage spans Miami (52), Kosciusko (47), Vigo (42), Montgomery (39), Floyd (36), Hamilton (33), Parke (31), Perry (29), Warrick (27), Jennings (26), Greene (25), Shelby (23) , plus 73 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Rush | 466 | 466 | 163 |
| Brown | 233 | 233 | 82 |
| Bartholomew | 155 | 155 | 54 |
| Vermillion | 117 | 117 | 41 |
| Tippecanoe | 93 | 93 | 33 |
| White | 78 | 78 | 27 |
| Tipton | 67 | 67 | 23 |
| Sullivan | 58 | 58 | 20 |
| Miami | 52 | 52 | 18 |
| Kosciusko | 47 | 47 | 16 |
| All districts (93) | 2,385 | 2,385 | 835 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Rush | 466 | 466 | 163 |
| Brown | 233 | 233 | 82 |
| Bartholomew | 155 | 155 | 54 |
| Vermillion | 117 | 117 | 41 |
| Tippecanoe | 93 | 93 | 33 |
| White | 78 | 78 | 27 |
| Tipton | 67 | 67 | 23 |
| Sullivan | 58 | 58 | 20 |
| Miami | 52 | 52 | 18 |
| Kosciusko | 47 | 47 | 16 |
| Vigo | 42 | 42 | 15 |
| Montgomery | 39 | 39 | 14 |
| Floyd | 36 | 36 | 13 |
| Hamilton | 33 | 33 | 12 |
| Parke | 31 | 31 | 11 |
| Perry | 29 | 29 | 10 |
| Warrick | 27 | 27 | 9 |
| Jennings | 26 | 26 | 9 |
| Greene | 25 | 25 | 9 |
| Shelby | 23 | 23 | 8 |
| Howard | 22 | 22 | 8 |
| Union | 21 | 21 | 7 |
| Pike | 20 | 20 | 7 |
| Daviess | 19 | 19 | 7 |
| Owen | 19 | 19 | 7 |
| Lake | 18 | 18 | 6 |
| Lawrence | 17 | 17 | 6 |
| Noble | 17 | 17 | 6 |
| Madison | 16 | 16 | 6 |
| Gibson | 16 | 16 | 6 |
| Posey | 15 | 15 | 5 |
| Dubois | 15 | 15 | 5 |
| Scott | 14 | 14 | 5 |
| Franklin | 14 | 14 | 5 |
| Henry | 13 | 13 | 5 |
| Porter | 13 | 13 | 5 |
| Jay | 13 | 13 | 5 |
| Cass | 12 | 12 | 4 |
| Wabash | 12 | 12 | 4 |
| Putnam | 12 | 12 | 4 |
| Clark | 11 | 11 | 4 |
| Decatur | 11 | 11 | 4 |
| Jefferson | 11 | 11 | 4 |
| Randolph | 11 | 11 | 4 |
| Allen | 10 | 10 | 4 |
| Benton | 10 | 10 | 4 |
| Washington | 10 | 10 | 4 |
| Jackson | 10 | 10 | 4 |
| St. Joseph | 10 | 10 | 4 |
| Whitley | 9 | 9 | 3 |
| Switzerland | 9 | 9 | 3 |
| Marion | 9 | 9 | 3 |
| Ripley | 9 | 9 | 3 |
| Ohio | 9 | 9 | 3 |
| Hendricks | 8 | 8 | 3 |
| Delaware | 8 | 8 | 3 |
| Boone | 8 | 8 | 3 |
| Wells | 8 | 8 | 3 |
| Morgan | 8 | 8 | 3 |
| St Joseph | 8 | 8 | 3 |
| Monroe | 8 | 8 | 3 |
| Grant | 8 | 8 | 3 |
| Fayette | 7 | 7 | 2 |
| LaPorte | 7 | 7 | 2 |
| Carroll | 7 | 7 | 2 |
| LaGrange | 7 | 7 | 2 |
| Starke | 7 | 7 | 2 |
| Knox | 7 | 7 | 2 |
| Warren | 7 | 7 | 2 |
| Pulaski | 7 | 7 | 2 |
| Vanderburgh | 7 | 7 | 2 |
| Martin | 6 | 6 | 2 |
| Jasper | 6 | 6 | 2 |
| Clinton | 6 | 6 | 2 |
| Fulton | 6 | 6 | 2 |
| Blackford | 6 | 6 | 2 |
| Newton | 6 | 6 | 2 |
| Adams | 6 | 6 | 2 |
| Hancock | 6 | 6 | 2 |
| Harrison | 6 | 6 | 2 |
| Huntington | 6 | 6 | 2 |
| Clay | 6 | 6 | 2 |
| Crawford | 6 | 6 | 2 |
| Elkhart | 6 | 6 | 2 |
| DeKalb | 6 | 6 | 2 |
| Fountain | 5 | 5 | 2 |
| Marshall | 5 | 5 | 2 |
| Wayne | 5 | 5 | 2 |
| Spencer | 5 | 5 | 2 |
| Johnson | 5 | 5 | 2 |
| Steuben | 5 | 5 | 2 |
| Orange | 5 | 5 | 2 |
| Dearborn | 5 | 5 | 2 |
| All districts (93) | 2,385 | 2,385 | 835 |
The Office Cleaning Services database for Indiana, United States includes 2,385+ 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 Indiana, United States contains 2,385+ 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 Indiana, 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 Indiana, 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.
The World Wide Data Database for Indiana, United States is a 2,385+ verified records directory of world wide data businesses — aggregated through the Data2Sales AI engine, cross-referenced across public business registries, official company websites, licensed directory partners, and social platforms, then re-verified monthly so every record in the export is deliverable on day one.
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 03:37 AM
Rows (Regular):
1,073
Rows (Extended):
2,385
Category:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
