Install Data2Sales AI
Faster access, offline browsing, and a one-tap shortcut on your home screen.
This dataset covers 2,643 verified records spread across 79+ districts in Uttar Pradesh. 2,643 records carry a verified phone number and 925 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Shravasti (534 listings), Shamli (267 listings), Hardoi (178 listings), Auraiya (133 listings), Azamgarh (107 listings), Balrampur (89 listings), Bareilly (76 listings), and Maharajganj (67 listings).
Additional coverage spans Sitapur (59), Hamirpur (53), Moradabad (49), Mainpuri (44), Raebareli (41), Shrawasti (38), Siddharthnagar (36), Shahjahanpur (33), Kushinagar (31), Prayagraj (30), Pilibhit (28), Mau (27) , plus 59 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Shravasti | 534 | 534 | 187 |
| Shamli | 267 | 267 | 93 |
| Hardoi | 178 | 178 | 62 |
| Auraiya | 133 | 133 | 47 |
| Azamgarh | 107 | 107 | 37 |
| Balrampur | 89 | 89 | 31 |
| Bareilly | 76 | 76 | 27 |
| Maharajganj | 67 | 67 | 23 |
| Sitapur | 59 | 59 | 21 |
| Hamirpur | 53 | 53 | 19 |
| All districts (79) | 2,643 | 2,643 | 925 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Shravasti | 534 | 534 | 187 |
| Shamli | 267 | 267 | 93 |
| Hardoi | 178 | 178 | 62 |
| Auraiya | 133 | 133 | 47 |
| Azamgarh | 107 | 107 | 37 |
| Balrampur | 89 | 89 | 31 |
| Bareilly | 76 | 76 | 27 |
| Maharajganj | 67 | 67 | 23 |
| Sitapur | 59 | 59 | 21 |
| Hamirpur | 53 | 53 | 19 |
| Moradabad | 49 | 49 | 17 |
| Mainpuri | 44 | 44 | 15 |
| Raebareli | 41 | 41 | 14 |
| Shrawasti | 38 | 38 | 13 |
| Siddharthnagar | 36 | 36 | 13 |
| Shahjahanpur | 33 | 33 | 12 |
| Kushinagar | 31 | 31 | 11 |
| Prayagraj | 30 | 30 | 11 |
| Pilibhit | 28 | 28 | 10 |
| Mau | 27 | 27 | 9 |
| Bahraich | 25 | 25 | 9 |
| Mathura | 24 | 24 | 8 |
| Ballia | 23 | 23 | 8 |
| Lalitpur | 22 | 22 | 8 |
| Lakhimpur Kheri | 21 | 21 | 7 |
| Varanasi | 21 | 21 | 7 |
| Agra | 20 | 20 | 7 |
| Jaunpur | 19 | 19 | 7 |
| Kaushambi | 18 | 18 | 6 |
| Muzaffarnagar | 18 | 18 | 6 |
| Ambedkar Nagar | 17 | 17 | 6 |
| Budaun | 17 | 17 | 6 |
| Deoria | 16 | 16 | 6 |
| Ghaziabad | 16 | 16 | 6 |
| Amethi | 15 | 15 | 5 |
| Hapur | 15 | 15 | 5 |
| Sambhal | 14 | 14 | 5 |
| Sant Kabir Nagar | 14 | 14 | 5 |
| Bulandshahr | 14 | 14 | 5 |
| Rampur | 13 | 13 | 5 |
| Gorakhpur | 13 | 13 | 5 |
| Firozabad | 13 | 13 | 5 |
| Hathras | 12 | 12 | 4 |
| Bijnor | 12 | 12 | 4 |
| Gautam Buddha Nagar | 12 | 12 | 4 |
| Kheri | 12 | 12 | 4 |
| Sultanpur | 11 | 11 | 4 |
| Aligarh | 11 | 11 | 4 |
| Baghpat | 11 | 11 | 4 |
| Pratapgarh | 11 | 11 | 4 |
| Kanpur Nagar | 10 | 10 | 4 |
| Chandauli | 10 | 10 | 4 |
| Amroha | 10 | 10 | 4 |
| Kasganj | 10 | 10 | 4 |
| Lucknow | 10 | 10 | 4 |
| Meerut | 10 | 10 | 4 |
| Basti | 9 | 9 | 3 |
| Etawah | 9 | 9 | 3 |
| Farrukhabad | 9 | 9 | 3 |
| Allahabad | 9 | 9 | 3 |
| Kanpur | 9 | 9 | 3 |
| Kanpur Dehat | 9 | 9 | 3 |
| Sonbhadra | 8 | 8 | 3 |
| Ghazipur | 8 | 8 | 3 |
| Chitrakoot | 8 | 8 | 3 |
| Mirzapur | 8 | 8 | 3 |
| Ayodhya | 8 | 8 | 3 |
| Saharanpur | 8 | 8 | 3 |
| Etah | 8 | 8 | 3 |
| Bhadohi | 8 | 8 | 3 |
| Gonda | 8 | 8 | 3 |
| Banda | 8 | 8 | 3 |
| Mahoba | 7 | 7 | 2 |
| Jalaun | 7 | 7 | 2 |
| Barabanki | 7 | 7 | 2 |
| Kannauj | 7 | 7 | 2 |
| Jhansi | 7 | 7 | 2 |
| Unnao | 7 | 7 | 2 |
| Fatehpur | 7 | 7 | 2 |
| All districts (79) | 2,643 | 2,643 | 925 |
The Buy Furniture Retail stores database includes 2,643+ verified Buy Furniture Retail 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.
Counting only operational sites, the Buy Furniture Retail footprint in Uttar Pradesh, India sits at about 2,643+ stores this 2026. The CSV on this page covers all of them — phones, hours, GPS, the lot.
This page IS the download point. The Buy Furniture Retail stores CSV for Uttar Pradesh, India ships immediately after payment and includes all verified store-level fields.
Every record in the Buy Furniture Retail stores dataset includes: Buy Furniture Retail 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 Buy Furniture Retail 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 Buy Furniture Retail 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 Buy Furniture Retail 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 Buy Furniture Retail 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 2,643+ 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 08, 2026 13:38 PM
Published:
May 11, 2026 02:29 AM
Rows (Regular):
1,189
Rows (Extended):
2,643
Category:
Tags:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
