Install Data2Sales AI
Faster access, offline browsing, and a one-tap shortcut on your home screen.
This dataset covers 2,512 verified records spread across 72+ districts in Wisconsin. 2,512 records carry a verified phone number and 879 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Buffalo (517 listings), Crawford (258 listings), La Crosse (172 listings), Pepin (129 listings), Polk (103 listings), Dane (86 listings), Shawano (74 listings), and Langlade (65 listings).
Additional coverage spans Brown (57), Walworth (52), Trempealeau (47), Manitowoc (43), Juneau (40), Racine (37), Menominee (34), Wood (32), Lafayette (30), Vernon (29), Portage (27), Rock (26) , plus 52 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Buffalo | 517 | 517 | 181 |
| Crawford | 258 | 258 | 90 |
| La Crosse | 172 | 172 | 60 |
| Pepin | 129 | 129 | 45 |
| Polk | 103 | 103 | 36 |
| Dane | 86 | 86 | 30 |
| Shawano | 74 | 74 | 26 |
| Langlade | 65 | 65 | 23 |
| Brown | 57 | 57 | 20 |
| Walworth | 52 | 52 | 18 |
| All districts (72) | 2,512 | 2,512 | 879 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Buffalo | 517 | 517 | 181 |
| Crawford | 258 | 258 | 90 |
| La Crosse | 172 | 172 | 60 |
| Pepin | 129 | 129 | 45 |
| Polk | 103 | 103 | 36 |
| Dane | 86 | 86 | 30 |
| Shawano | 74 | 74 | 26 |
| Langlade | 65 | 65 | 23 |
| Brown | 57 | 57 | 20 |
| Walworth | 52 | 52 | 18 |
| Trempealeau | 47 | 47 | 16 |
| Manitowoc | 43 | 43 | 15 |
| Juneau | 40 | 40 | 14 |
| Racine | 37 | 37 | 13 |
| Menominee | 34 | 34 | 12 |
| Wood | 32 | 32 | 11 |
| Lafayette | 30 | 30 | 11 |
| Vernon | 29 | 29 | 10 |
| Portage | 27 | 27 | 9 |
| Rock | 26 | 26 | 9 |
| Kenosha | 25 | 25 | 9 |
| Barron | 23 | 23 | 8 |
| Taylor | 22 | 22 | 8 |
| Waukesha | 22 | 22 | 8 |
| Sawyer | 21 | 21 | 7 |
| Burnett | 20 | 20 | 7 |
| Lincoln | 19 | 19 | 7 |
| Waushara | 18 | 18 | 6 |
| Ozaukee | 18 | 18 | 6 |
| Forest | 17 | 17 | 6 |
| Rusk | 17 | 17 | 6 |
| Calumet | 16 | 16 | 6 |
| St. Croix | 16 | 16 | 6 |
| Iron | 15 | 15 | 5 |
| Vilas | 15 | 15 | 5 |
| Marquette | 14 | 14 | 5 |
| Iowa | 14 | 14 | 5 |
| Washburn | 14 | 14 | 5 |
| Kewaunee | 13 | 13 | 5 |
| Door | 13 | 13 | 5 |
| Monroe | 13 | 13 | 5 |
| Marinette | 12 | 12 | 4 |
| Jefferson | 12 | 12 | 4 |
| Ashland | 12 | 12 | 4 |
| Sauk | 11 | 11 | 4 |
| Clark | 11 | 11 | 4 |
| Waupaca | 11 | 11 | 4 |
| Dunn | 11 | 11 | 4 |
| Green | 11 | 11 | 4 |
| Sheboygan | 10 | 10 | 4 |
| Winnebago | 10 | 10 | 4 |
| Bayfield | 10 | 10 | 4 |
| Grant | 10 | 10 | 4 |
| Outagamie | 10 | 10 | 4 |
| Price | 9 | 9 | 3 |
| Florence | 9 | 9 | 3 |
| Columbia | 9 | 9 | 3 |
| Milwaukee | 9 | 9 | 3 |
| Pierce | 9 | 9 | 3 |
| Marathon | 9 | 9 | 3 |
| Richland | 9 | 9 | 3 |
| Jackson | 8 | 8 | 3 |
| Oneida | 8 | 8 | 3 |
| Dodge | 8 | 8 | 3 |
| Eau Claire | 8 | 8 | 3 |
| Oconto | 8 | 8 | 3 |
| Chippewa | 8 | 8 | 3 |
| Washington | 8 | 8 | 3 |
| Fond du Lac | 8 | 8 | 3 |
| Douglas | 7 | 7 | 2 |
| Adams | 7 | 7 | 2 |
| Green Lake | 7 | 7 | 2 |
| All districts (72) | 2,512 | 2,512 | 879 |
The Wisconsin-Wide Clothing stores database includes 2,512+ verified Wisconsin-Wide Clothing stores in Wisconsin, 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.
Wisconsin-Wide Clothing currently operates 2,512+ stores in Wisconsin, United States (as of 2026). Buy access on this page and you get the master CSV with every store's verified contact + geolocation row.
Right on this page — click Buy / Add to Cart and you'll receive a Data2Sales AI-verified Wisconsin-Wide Clothing stores CSV covering all of Wisconsin, United States within seconds. Every row is human-checked.
Every record in the Wisconsin-Wide Clothing stores dataset includes: Wisconsin-Wide Clothing store name, Street address, City, State / Region, Postal code, Country, Phone number, Website URL and more. The file is delivered as a UTF-8 CSV that opens in Excel, Google Sheets or any standard CRM importer.
Triple-source verification: the Wisconsin-Wide Clothing store locator, Google Maps data and licensed B2B directories all have to agree before a record makes the CSV. Dead phones and 'permanently closed' markers prune the list every month.
Yes. The Wisconsin-Wide Clothing 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 Wisconsin-Wide Clothing 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 Wisconsin-Wide Clothing stores — not a stale snapshot. You also get 7 days of unlimited re-downloads from a secure link sent to your email.
This World Wide Data list covers 2,512+ verified records operating in Wisconsin, United States. Every entry is compiled by the Data2Sales AI engine from multiple verified sources, de-duplicated against our master index, and refreshed each month — saving sales, marketing, and research teams the manual cleanup normally needed before outreach.
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 04:25 AM
Rows (Regular):
1,130
Rows (Extended):
2,512
Category:
Tags:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
