Install Data2Sales AI
Faster access, offline browsing, and a one-tap shortcut on your home screen.
This dataset covers 2,627 verified records spread across 79+ districts in Uttar Pradesh. 2,627 records carry a verified phone number and 919 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Gautam Buddha Nagar (530 listings), Unnao (265 listings), Mirzapur (177 listings), Mau (133 listings), Agra (106 listings), Banda (88 listings), Chitrakoot (76 listings), and Sitapur (66 listings).
Additional coverage spans Saharanpur (59), Fatehpur (53), Hardoi (48), Auraiya (44), Shamli (41), Barabanki (38), Farrukhabad (35), Gonda (33), Budaun (31), Pratapgarh (29), Basti (28), Sultanpur (27) , plus 59 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Gautam Buddha Nagar | 530 | 530 | 186 |
| Unnao | 265 | 265 | 93 |
| Mirzapur | 177 | 177 | 62 |
| Mau | 133 | 133 | 47 |
| Agra | 106 | 106 | 37 |
| Banda | 88 | 88 | 31 |
| Chitrakoot | 76 | 76 | 27 |
| Sitapur | 66 | 66 | 23 |
| Saharanpur | 59 | 59 | 21 |
| Fatehpur | 53 | 53 | 19 |
| All districts (79) | 2,627 | 2,627 | 919 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Gautam Buddha Nagar | 530 | 530 | 186 |
| Unnao | 265 | 265 | 93 |
| Mirzapur | 177 | 177 | 62 |
| Mau | 133 | 133 | 47 |
| Agra | 106 | 106 | 37 |
| Banda | 88 | 88 | 31 |
| Chitrakoot | 76 | 76 | 27 |
| Sitapur | 66 | 66 | 23 |
| Saharanpur | 59 | 59 | 21 |
| Fatehpur | 53 | 53 | 19 |
| Hardoi | 48 | 48 | 17 |
| Auraiya | 44 | 44 | 15 |
| Shamli | 41 | 41 | 14 |
| Barabanki | 38 | 38 | 13 |
| Farrukhabad | 35 | 35 | 12 |
| Gonda | 33 | 33 | 12 |
| Budaun | 31 | 31 | 11 |
| Pratapgarh | 29 | 29 | 10 |
| Basti | 28 | 28 | 10 |
| Sultanpur | 27 | 27 | 9 |
| Chandauli | 25 | 25 | 9 |
| Deoria | 24 | 24 | 8 |
| Sambhal | 23 | 23 | 8 |
| Gorakhpur | 22 | 22 | 8 |
| Amethi | 21 | 21 | 7 |
| Firozabad | 20 | 20 | 7 |
| Jaunpur | 20 | 20 | 7 |
| Allahabad | 19 | 19 | 7 |
| Shahjahanpur | 18 | 18 | 6 |
| Sonbhadra | 18 | 18 | 6 |
| Ballia | 17 | 17 | 6 |
| Mathura | 17 | 17 | 6 |
| Ghazipur | 16 | 16 | 6 |
| Kheri | 16 | 16 | 6 |
| Lalitpur | 15 | 15 | 5 |
| Amroha | 15 | 15 | 5 |
| Etah | 14 | 14 | 5 |
| Kaushambi | 14 | 14 | 5 |
| Etawah | 14 | 14 | 5 |
| Maharajganj | 13 | 13 | 5 |
| Bahraich | 13 | 13 | 5 |
| Meerut | 13 | 13 | 5 |
| Muzaffarnagar | 12 | 12 | 4 |
| Kasganj | 12 | 12 | 4 |
| Kanpur | 12 | 12 | 4 |
| Lucknow | 12 | 12 | 4 |
| Hapur | 11 | 11 | 4 |
| Siddharthnagar | 11 | 11 | 4 |
| Varanasi | 11 | 11 | 4 |
| Rampur | 11 | 11 | 4 |
| Ghaziabad | 10 | 10 | 4 |
| Aligarh | 10 | 10 | 4 |
| Baghpat | 10 | 10 | 4 |
| Bijnor | 10 | 10 | 4 |
| Hathras | 10 | 10 | 4 |
| Kanpur Nagar | 9 | 9 | 3 |
| Jhansi | 9 | 9 | 3 |
| Balrampur | 9 | 9 | 3 |
| Ambedkar Nagar | 9 | 9 | 3 |
| Bareilly | 9 | 9 | 3 |
| Shravasti | 9 | 9 | 3 |
| Kannauj | 9 | 9 | 3 |
| Azamgarh | 8 | 8 | 3 |
| Shrawasti | 8 | 8 | 3 |
| Sant Kabir Nagar | 8 | 8 | 3 |
| Kanpur Dehat | 8 | 8 | 3 |
| Mainpuri | 8 | 8 | 3 |
| Kushinagar | 8 | 8 | 3 |
| Bulandshahr | 8 | 8 | 3 |
| Prayagraj | 8 | 8 | 3 |
| Moradabad | 8 | 8 | 3 |
| Bhadohi | 7 | 7 | 2 |
| Hamirpur | 7 | 7 | 2 |
| Mahoba | 7 | 7 | 2 |
| Ayodhya | 7 | 7 | 2 |
| Pilibhit | 7 | 7 | 2 |
| Raebareli | 7 | 7 | 2 |
| Lakhimpur Kheri | 7 | 7 | 2 |
| Jalaun | 7 | 7 | 2 |
| All districts (79) | 2,627 | 2,627 | 919 |
The Verified Shopify stores database includes 2,627+ verified Shopify 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.
Verified Shopify currently operates 2,627+ 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.
Right on this page — click Buy / Add to Cart and you'll receive a Data2Sales AI-verified Shopify stores CSV covering all of Uttar Pradesh, India within seconds. Every row is human-checked.
The CSV ships with one row per Verified Shopify location, columns covering Verified Shopify store name, Street address, City, State / Region, Postal code, Country, Phone number, Website URL plus website, opening-hours window, ratings and review counts. UTF-8 encoded — imports cleanly into HubSpot, Salesforce, Zoho or any CRM.
Each Verified Shopify row goes through phone validation, address cross-check against Google Maps and a check against the official Verified Shopify Uttar Pradesh, India locator. Records that fail any of those drop before you ever see them.
Yes. The Verified Shopify 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 Verified Shopify 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 Shopify 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 2,627+ verified records operating in Uttar Pradesh, India. 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.
Last Update:
Jul 08, 2026 13:38 PM
Published:
Jul 06, 2026 04:22 AM
Rows (Regular):
1,182
Rows (Extended):
2,627
Category:
Tags:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
