Data2Sales AI
4.8
★★★★★
★★★★★
Verified buyers
Unlock actionable insights and supercharge your sales pipeline. Download this verified, analysis-ready dataset today.
This dataset covers 16,108 verified records spread across 79+ districts in Uttar Pradesh. 16,108 records carry a verified phone number and 5,638 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Bareilly (3,252 listings), Ayodhya (1,626 listings), Mahoba (1,084 listings), Jalaun (813 listings), Azamgarh (650 listings), Ghaziabad (542 listings), Gautam Buddha Nagar (465 listings), and Maharajganj (407 listings).
Additional coverage spans Gonda (361), Bhadohi (325), Kanpur Dehat (296), Unnao (271), Pilibhit (250), Kaushambi (232), Kannauj (217), Kushinagar (203), Banda (191), Mainpuri (181), Jhansi (171), Hamirpur (163) , plus 59 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Bareilly | 3,252 | 3,252 | 1,138 |
| Ayodhya | 1,626 | 1,626 | 569 |
| Mahoba | 1,084 | 1,084 | 379 |
| Jalaun | 813 | 813 | 285 |
| Azamgarh | 650 | 650 | 228 |
| Ghaziabad | 542 | 542 | 190 |
| Gautam Buddha Nagar | 465 | 465 | 163 |
| Maharajganj | 407 | 407 | 142 |
| Gonda | 361 | 361 | 126 |
| Bhadohi | 325 | 325 | 114 |
| All districts (79) | 16,108 | 16,108 | 5,638 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Bareilly | 3,252 | 3,252 | 1,138 |
| Ayodhya | 1,626 | 1,626 | 569 |
| Mahoba | 1,084 | 1,084 | 379 |
| Jalaun | 813 | 813 | 285 |
| Azamgarh | 650 | 650 | 228 |
| Ghaziabad | 542 | 542 | 190 |
| Gautam Buddha Nagar | 465 | 465 | 163 |
| Maharajganj | 407 | 407 | 142 |
| Gonda | 361 | 361 | 126 |
| Bhadohi | 325 | 325 | 114 |
| Kanpur Dehat | 296 | 296 | 104 |
| Unnao | 271 | 271 | 95 |
| Pilibhit | 250 | 250 | 88 |
| Kaushambi | 232 | 232 | 81 |
| Kannauj | 217 | 217 | 76 |
| Kushinagar | 203 | 203 | 71 |
| Banda | 191 | 191 | 67 |
| Mainpuri | 181 | 181 | 63 |
| Jhansi | 171 | 171 | 60 |
| Hamirpur | 163 | 163 | 57 |
| Kanpur Nagar | 155 | 155 | 54 |
| Prayagraj | 148 | 148 | 52 |
| Hathras | 141 | 141 | 49 |
| Etah | 136 | 136 | 48 |
| Shrawasti | 130 | 130 | 46 |
| Varanasi | 125 | 125 | 44 |
| Lalitpur | 120 | 120 | 42 |
| Raebareli | 116 | 116 | 41 |
| Rampur | 112 | 112 | 39 |
| Moradabad | 108 | 108 | 38 |
| Bijnor | 105 | 105 | 37 |
| Baghpat | 102 | 102 | 36 |
| Bahraich | 99 | 99 | 35 |
| Kheri | 96 | 96 | 34 |
| Aligarh | 93 | 93 | 33 |
| Basti | 90 | 90 | 32 |
| Kanpur | 88 | 88 | 31 |
| Lucknow | 86 | 86 | 30 |
| Kasganj | 83 | 83 | 29 |
| Balrampur | 81 | 81 | 28 |
| Bulandshahr | 79 | 79 | 28 |
| Amroha | 77 | 77 | 27 |
| Sant Kabir Nagar | 76 | 76 | 27 |
| Shravasti | 74 | 74 | 26 |
| Lakhimpur Kheri | 72 | 72 | 25 |
| Meerut | 71 | 71 | 25 |
| Etawah | 69 | 69 | 24 |
| Pratapgarh | 68 | 68 | 24 |
| Mathura | 66 | 66 | 23 |
| Shahjahanpur | 65 | 65 | 23 |
| Jaunpur | 64 | 64 | 22 |
| Muzaffarnagar | 63 | 63 | 22 |
| Ballia | 61 | 61 | 21 |
| Barabanki | 60 | 60 | 21 |
| Ghazipur | 59 | 59 | 21 |
| Amethi | 58 | 58 | 20 |
| Siddharthnagar | 57 | 57 | 20 |
| Budaun | 56 | 56 | 20 |
| Sambhal | 55 | 55 | 19 |
| Hapur | 54 | 54 | 19 |
| Farrukhabad | 53 | 53 | 19 |
| Deoria | 52 | 52 | 18 |
| Mau | 52 | 52 | 18 |
| Sonbhadra | 51 | 51 | 18 |
| Allahabad | 50 | 50 | 18 |
| Agra | 49 | 49 | 17 |
| Chitrakoot | 49 | 49 | 17 |
| Mirzapur | 48 | 48 | 17 |
| Auraiya | 47 | 47 | 16 |
| Shamli | 46 | 46 | 16 |
| Saharanpur | 46 | 46 | 16 |
| Hardoi | 45 | 45 | 16 |
| Chandauli | 45 | 45 | 16 |
| Ambedkar Nagar | 44 | 44 | 15 |
| Sitapur | 43 | 43 | 15 |
| Sultanpur | 43 | 43 | 15 |
| Gorakhpur | 43 | 43 | 15 |
| Fatehpur | 42 | 42 | 15 |
| Firozabad | 42 | 42 | 15 |
| All districts (79) | 16,108 | 16,108 | 5,638 |
The Finance Departments database for Uttar Pradesh, India includes 16,108+ 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.
The Finance Departments database for Uttar Pradesh, India contains 16,108+ 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 Finance Departments 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 finance departments footprint in Uttar Pradesh, India.
Yes. The Finance Departments 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.
Data2Sales AI's World Wide Data database for Uttar Pradesh, India consolidates 16,108+ 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:
Aug 07, 2026 05:45 AM
Published:
May 11, 2026 02:28 AM
Rows (Regular):
8,054
Rows (Extended):
16,108
Category:
Tags
No tags