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This dataset covers 21 verified records spread across 13+ cities in Uttar Pradesh. 21 records carry a verified phone number and 5 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density cities are Ghaziabad (6 listings), Varanasi (2 listings), Ballia (2 listings), Siddharthnagar (2 listings), Hathras (1 listings), Jaunpur (1 listings), Sant Kabir Nagar (1 listings), and Chandauli (1 listings).
Additional coverage spans Lucknow (1), Prayagraj (1), Agra (1), Rampur (1), Shahjahanpur (1) .
| Cities | Total | With mobile | With website |
|---|---|---|---|
| Ghaziabad | 6 | 6 | 4 |
| Varanasi | 2 | 2 | 0 |
| Ballia | 2 | 2 | 0 |
| Siddharthnagar | 2 | 2 | 1 |
| Hathras | 1 | 1 | 0 |
| Jaunpur | 1 | 1 | 0 |
| Sant Kabir Nagar | 1 | 1 | 0 |
| Chandauli | 1 | 1 | 0 |
| Lucknow | 1 | 1 | 0 |
| Prayagraj | 1 | 1 | 0 |
| All cities (13) | 21 | 21 | 5 |
| Cities | Total | With mobile | With website |
|---|---|---|---|
| Ghaziabad | 6 | 6 | 4 |
| Varanasi | 2 | 2 | 0 |
| Ballia | 2 | 2 | 0 |
| Siddharthnagar | 2 | 2 | 1 |
| Hathras | 1 | 1 | 0 |
| Jaunpur | 1 | 1 | 0 |
| Sant Kabir Nagar | 1 | 1 | 0 |
| Chandauli | 1 | 1 | 0 |
| Lucknow | 1 | 1 | 0 |
| Prayagraj | 1 | 1 | 0 |
| Agra | 1 | 1 | 0 |
| Rampur | 1 | 1 | 0 |
| Shahjahanpur | 1 | 1 | 0 |
| All cities (13) | 21 | 21 | 5 |
The Sporting Goods stores database includes 4,724+ verified Sporting Goods stores in Uttar Pradesh, India 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.
Umar (IN) bought 1 week ago · Nazir (IN) bought 1 week ago · Ruchi (IN) bought 1 week ago · Rachel (IN) bought 2 weeks ago · Sharad (IN) bought 2 weeks ago
Sporting Goods currently operates 4,724+ stores in Uttar Pradesh, India (as of 2026). Buy access on this page and you get the master CSV with every store's verified contact + geolocation row.
Data2Sales AI hosts the most up-to-date Sporting Goods stores list for Uttar Pradesh, India; checkout above delivers a same-second CSV with addresses, phones, GPS and operating hours.
Every record in the Sporting Goods stores dataset includes: Sporting Goods 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.
Each Sporting Goods row goes through phone validation, address cross-check against Google Maps and a check against the official Sporting Goods Uttar Pradesh, India locator. Records that fail any of those drop before you ever see them.
Yes. The Sporting Goods 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 Sporting Goods 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 Sporting Goods stores — not a stale snapshot. You also get 7 days of unlimited re-downloads from a secure link sent to your email.
Data2Sales AI's World Wide Data database for Uttar Pradesh, India consolidates 4,724+ verified records into a single, verified contact list. The engine crosses multiple sources — official websites, business registries, social profiles, licensed directories — and validates each record monthly, so your sales pipeline starts with accurate data instead of a spreadsheet of guesses.
Last Update:
Jul 06, 2026 04:20 AM
Published:
May 11, 2026 02:29 AM
Rows (Regular):
2,126
Rows (Extended):
4,724
Category:
Tags:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
