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This dataset covers 3,412 verified records spread across 79+ districts in Uttar Pradesh. 3,412 records carry a verified phone number and 1,194 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Banda (689 listings), Gautam Buddha Nagar (344 listings), Shamli (230 listings), Sambhal (172 listings), Hardoi (138 listings), Sonbhadra (115 listings), Unnao (98 listings), and Fatehpur (86 listings).
Additional coverage spans Allahabad (77), Ambedkar Nagar (69), Jaunpur (63), Firozabad (57), Gorakhpur (53), Gonda (49), Shahjahanpur (46), Chandauli (43), Mirzapur (41), Mathura (38), Maharajganj (36), Sultanpur (34) , plus 59 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Banda | 689 | 689 | 241 |
| Gautam Buddha Nagar | 344 | 344 | 120 |
| Shamli | 230 | 230 | 81 |
| Sambhal | 172 | 172 | 60 |
| Hardoi | 138 | 138 | 48 |
| Sonbhadra | 115 | 115 | 40 |
| Unnao | 98 | 98 | 34 |
| Fatehpur | 86 | 86 | 30 |
| Allahabad | 77 | 77 | 27 |
| Ambedkar Nagar | 69 | 69 | 24 |
| All districts (79) | 3,412 | 3,412 | 1,194 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Banda | 689 | 689 | 241 |
| Gautam Buddha Nagar | 344 | 344 | 120 |
| Shamli | 230 | 230 | 81 |
| Sambhal | 172 | 172 | 60 |
| Hardoi | 138 | 138 | 48 |
| Sonbhadra | 115 | 115 | 40 |
| Unnao | 98 | 98 | 34 |
| Fatehpur | 86 | 86 | 30 |
| Allahabad | 77 | 77 | 27 |
| Ambedkar Nagar | 69 | 69 | 24 |
| Jaunpur | 63 | 63 | 22 |
| Firozabad | 57 | 57 | 20 |
| Gorakhpur | 53 | 53 | 19 |
| Gonda | 49 | 49 | 17 |
| Shahjahanpur | 46 | 46 | 16 |
| Chandauli | 43 | 43 | 15 |
| Mirzapur | 41 | 41 | 14 |
| Mathura | 38 | 38 | 13 |
| Maharajganj | 36 | 36 | 13 |
| Sultanpur | 34 | 34 | 12 |
| Ghazipur | 33 | 33 | 12 |
| Ballia | 31 | 31 | 11 |
| Barabanki | 30 | 30 | 11 |
| Basti | 29 | 29 | 10 |
| Bulandshahr | 28 | 28 | 10 |
| Sitapur | 26 | 26 | 9 |
| Budaun | 26 | 26 | 9 |
| Deoria | 25 | 25 | 9 |
| Kheri | 24 | 24 | 8 |
| Auraiya | 23 | 23 | 8 |
| Siddharthnagar | 22 | 22 | 8 |
| Etah | 22 | 22 | 8 |
| Kushinagar | 21 | 21 | 7 |
| Amethi | 20 | 20 | 7 |
| Mau | 20 | 20 | 7 |
| Raebareli | 19 | 19 | 7 |
| Rampur | 19 | 19 | 7 |
| Saharanpur | 18 | 18 | 6 |
| Kanpur Nagar | 18 | 18 | 6 |
| Moradabad | 17 | 17 | 6 |
| Bijnor | 17 | 17 | 6 |
| Chitrakoot | 16 | 16 | 6 |
| Farrukhabad | 16 | 16 | 6 |
| Hapur | 16 | 16 | 6 |
| Prayagraj | 15 | 15 | 5 |
| Kannauj | 15 | 15 | 5 |
| Shrawasti | 15 | 15 | 5 |
| Lakhimpur Kheri | 14 | 14 | 5 |
| Kanpur Dehat | 14 | 14 | 5 |
| Amroha | 14 | 14 | 5 |
| Shravasti | 14 | 14 | 5 |
| Meerut | 13 | 13 | 5 |
| Etawah | 13 | 13 | 5 |
| Bhadohi | 13 | 13 | 5 |
| Varanasi | 13 | 13 | 5 |
| Ayodhya | 12 | 12 | 4 |
| Kanpur | 12 | 12 | 4 |
| Lalitpur | 12 | 12 | 4 |
| Balrampur | 12 | 12 | 4 |
| Bahraich | 11 | 11 | 4 |
| Muzaffarnagar | 11 | 11 | 4 |
| Pilibhit | 11 | 11 | 4 |
| Lucknow | 11 | 11 | 4 |
| Mahoba | 11 | 11 | 4 |
| Kasganj | 11 | 11 | 4 |
| Mainpuri | 10 | 10 | 4 |
| Hamirpur | 10 | 10 | 4 |
| Ghaziabad | 10 | 10 | 4 |
| Jalaun | 10 | 10 | 4 |
| Pratapgarh | 10 | 10 | 4 |
| Jhansi | 10 | 10 | 4 |
| Bareilly | 10 | 10 | 4 |
| Sant Kabir Nagar | 9 | 9 | 3 |
| Baghpat | 9 | 9 | 3 |
| Azamgarh | 9 | 9 | 3 |
| Aligarh | 9 | 9 | 3 |
| Kaushambi | 9 | 9 | 3 |
| Hathras | 9 | 9 | 3 |
| Agra | 7 | 7 | 2 |
| All districts (79) | 3,412 | 3,412 | 1,194 |
The Ice Cream Parlors database for Uttar Pradesh, India includes 3,412+ 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.
Omar (IN) bought 19 hours ago · Radhika (IN) bought 1 day ago · Geetanjali (IN) bought 1 day ago · Runjhun (IN) bought 2 days ago · Jaswant (IN) bought 4 days ago
The Ice Cream Parlors database for Uttar Pradesh, India contains 3,412+ 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 Ice Cream Parlors database for Uttar Pradesh, India 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 ice cream parlors footprint in Uttar Pradesh, India.
Yes. The Ice Cream Parlors 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 Uttar Pradesh, India is a 3,412+ 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.
Last Update:
Aug 14, 2026 05:45 AM
Published:
May 11, 2026 02:28 AM
Rows (Regular):
1,706
Rows (Extended):
3,412
Category:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
