Data2Sales AI
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This dataset covers 3,462 verified records spread across 79+ districts in Uttar Pradesh. 3,462 records carry a verified phone number and 1,212 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Mirzapur (699 listings), Balrampur (349 listings), Farrukhabad (233 listings), Mau (175 listings), Gonda (140 listings), Hardoi (116 listings), Shamli (100 listings), and Kannauj (87 listings).
Additional coverage spans Kushinagar (78), Shravasti (70), Bhadohi (64), Shrawasti (58), Fatehpur (54), Prayagraj (50), Banda (47), Ambedkar Nagar (44), Raebareli (41), Ayodhya (39), Unnao (37), Agra (35) , plus 59 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Mirzapur | 699 | 699 | 245 |
| Balrampur | 349 | 349 | 122 |
| Farrukhabad | 233 | 233 | 82 |
| Mau | 175 | 175 | 61 |
| Gonda | 140 | 140 | 49 |
| Hardoi | 116 | 116 | 41 |
| Shamli | 100 | 100 | 35 |
| Kannauj | 87 | 87 | 30 |
| Kushinagar | 78 | 78 | 27 |
| Shravasti | 70 | 70 | 25 |
| All districts (79) | 3,462 | 3,462 | 1,212 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Mirzapur | 699 | 699 | 245 |
| Balrampur | 349 | 349 | 122 |
| Farrukhabad | 233 | 233 | 82 |
| Mau | 175 | 175 | 61 |
| Gonda | 140 | 140 | 49 |
| Hardoi | 116 | 116 | 41 |
| Shamli | 100 | 100 | 35 |
| Kannauj | 87 | 87 | 30 |
| Kushinagar | 78 | 78 | 27 |
| Shravasti | 70 | 70 | 25 |
| Bhadohi | 64 | 64 | 22 |
| Shrawasti | 58 | 58 | 20 |
| Fatehpur | 54 | 54 | 19 |
| Prayagraj | 50 | 50 | 18 |
| Banda | 47 | 47 | 16 |
| Ambedkar Nagar | 44 | 44 | 15 |
| Raebareli | 41 | 41 | 14 |
| Ayodhya | 39 | 39 | 14 |
| Unnao | 37 | 37 | 13 |
| Agra | 35 | 35 | 12 |
| Moradabad | 33 | 33 | 12 |
| Gautam Buddha Nagar | 32 | 32 | 11 |
| Ballia | 30 | 30 | 11 |
| Kheri | 29 | 29 | 10 |
| Kaushambi | 28 | 28 | 10 |
| Lucknow | 27 | 27 | 9 |
| Kasganj | 26 | 26 | 9 |
| Muzaffarnagar | 25 | 25 | 9 |
| Deoria | 24 | 24 | 8 |
| Baghpat | 23 | 23 | 8 |
| Ghaziabad | 23 | 23 | 8 |
| Aligarh | 22 | 22 | 8 |
| Shahjahanpur | 21 | 21 | 7 |
| Budaun | 21 | 21 | 7 |
| Ghazipur | 20 | 20 | 7 |
| Amethi | 19 | 19 | 7 |
| Hathras | 19 | 19 | 7 |
| Siddharthnagar | 18 | 18 | 6 |
| Basti | 18 | 18 | 6 |
| Sambhal | 17 | 17 | 6 |
| Lalitpur | 17 | 17 | 6 |
| Bijnor | 17 | 17 | 6 |
| Sultanpur | 16 | 16 | 6 |
| Chandauli | 16 | 16 | 6 |
| Bahraich | 16 | 16 | 6 |
| Rampur | 15 | 15 | 5 |
| Gorakhpur | 15 | 15 | 5 |
| Lakhimpur Kheri | 15 | 15 | 5 |
| Varanasi | 14 | 14 | 5 |
| Firozabad | 14 | 14 | 5 |
| Allahabad | 14 | 14 | 5 |
| Etawah | 13 | 13 | 5 |
| Meerut | 13 | 13 | 5 |
| Hapur | 13 | 13 | 5 |
| Amroha | 13 | 13 | 5 |
| Sonbhadra | 12 | 12 | 4 |
| Jaunpur | 12 | 12 | 4 |
| Maharajganj | 12 | 12 | 4 |
| Etah | 12 | 12 | 4 |
| Kanpur | 12 | 12 | 4 |
| Pratapgarh | 11 | 11 | 4 |
| Mathura | 11 | 11 | 4 |
| Kanpur Nagar | 11 | 11 | 4 |
| Jalaun | 11 | 11 | 4 |
| Bulandshahr | 11 | 11 | 4 |
| Bareilly | 11 | 11 | 4 |
| Sitapur | 10 | 10 | 4 |
| Azamgarh | 10 | 10 | 4 |
| Mahoba | 10 | 10 | 4 |
| Kanpur Dehat | 10 | 10 | 4 |
| Sant Kabir Nagar | 10 | 10 | 4 |
| Saharanpur | 10 | 10 | 4 |
| Mainpuri | 10 | 10 | 4 |
| Auraiya | 9 | 9 | 3 |
| Chitrakoot | 9 | 9 | 3 |
| Jhansi | 9 | 9 | 3 |
| Hamirpur | 9 | 9 | 3 |
| Barabanki | 9 | 9 | 3 |
| Pilibhit | 9 | 9 | 3 |
| All districts (79) | 3,462 | 3,462 | 1,212 |
The Religious Goods stores database includes 3,462+ verified Religious 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.
Our latest 2026 count shows 3,462+ live Religious Goods stores across Uttar Pradesh, India. Every entry on the downloadable CSV is verified and ships with phone, address, opening hours and Google coordinates.
This page IS the download point. The Religious Goods stores CSV for Uttar Pradesh, India ships immediately after payment and includes all verified store-level fields.
Each Religious Goods record carries the full operational profile: Religious Goods store name, Street address, City, State / Region, Postal code, Country, Phone number, Website URL along with website, hours, Google rating and review volume. CSV opens directly in Excel / Sheets / Power BI / Looker.
Each Religious Goods row goes through phone validation, address cross-check against Google Maps and a check against the official Religious Goods Uttar Pradesh, India locator. Records that fail any of those drop before you ever see them.
Yes. The Religious 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 Religious 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 Religious Goods 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 3,462+ 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):
1,558
Rows (Extended):
3,462
Category:
Tags
Roll-up datasets — broader coverage at a higher tier are highlighted below.