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This dataset covers 32,357 verified records spread across 79+ districts in Uttar Pradesh. 32,357 records carry a verified phone number and 11,325 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Hapur (6,533 listings), Gautam Buddha Nagar (3,266 listings), Mau (2,178 listings), Barabanki (1,633 listings), Siddharthnagar (1,307 listings), Sitapur (1,089 listings), Etah (933 listings), and Bulandshahr (817 listings).
Additional coverage spans Auraiya (726), Muzaffarnagar (653), Shamli (594), Hardoi (544), Ghazipur (503), Budaun (467), Mirzapur (436), Deoria (408), Sant Kabir Nagar (384), Sambhal (363), Sonbhadra (344), Amethi (327) , plus 59 more districts.
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Hapur | 6,533 | 6,533 | 2,287 |
| Gautam Buddha Nagar | 3,266 | 3,266 | 1,143 |
| Mau | 2,178 | 2,178 | 762 |
| Barabanki | 1,633 | 1,633 | 572 |
| Siddharthnagar | 1,307 | 1,307 | 457 |
| Sitapur | 1,089 | 1,089 | 381 |
| Etah | 933 | 933 | 327 |
| Bulandshahr | 817 | 817 | 286 |
| Auraiya | 726 | 726 | 254 |
| Muzaffarnagar | 653 | 653 | 229 |
| All districts (79) | 32,357 | 32,357 | 11,325 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Hapur | 6,533 | 6,533 | 2,287 |
| Gautam Buddha Nagar | 3,266 | 3,266 | 1,143 |
| Mau | 2,178 | 2,178 | 762 |
| Barabanki | 1,633 | 1,633 | 572 |
| Siddharthnagar | 1,307 | 1,307 | 457 |
| Sitapur | 1,089 | 1,089 | 381 |
| Etah | 933 | 933 | 327 |
| Bulandshahr | 817 | 817 | 286 |
| Auraiya | 726 | 726 | 254 |
| Muzaffarnagar | 653 | 653 | 229 |
| Shamli | 594 | 594 | 208 |
| Hardoi | 544 | 544 | 190 |
| Ghazipur | 503 | 503 | 176 |
| Budaun | 467 | 467 | 163 |
| Mirzapur | 436 | 436 | 153 |
| Deoria | 408 | 408 | 143 |
| Sant Kabir Nagar | 384 | 384 | 134 |
| Sambhal | 363 | 363 | 127 |
| Sonbhadra | 344 | 344 | 120 |
| Amethi | 327 | 327 | 114 |
| Allahabad | 311 | 311 | 109 |
| Ambedkar Nagar | 297 | 297 | 104 |
| Jaunpur | 284 | 284 | 99 |
| Kushinagar | 272 | 272 | 95 |
| Firozabad | 261 | 261 | 91 |
| Ballia | 251 | 251 | 88 |
| Gorakhpur | 242 | 242 | 85 |
| Fatehpur | 233 | 233 | 82 |
| Mathura | 225 | 225 | 79 |
| Chandauli | 218 | 218 | 76 |
| Sultanpur | 211 | 211 | 74 |
| Shahjahanpur | 204 | 204 | 71 |
| Maharajganj | 198 | 198 | 69 |
| Amroha | 192 | 192 | 67 |
| Meerut | 187 | 187 | 65 |
| Banda | 181 | 181 | 63 |
| Etawah | 177 | 177 | 62 |
| Kasganj | 172 | 172 | 60 |
| Azamgarh | 168 | 168 | 59 |
| Lucknow | 163 | 163 | 57 |
| Saharanpur | 159 | 159 | 56 |
| Kanpur | 156 | 156 | 55 |
| Agra | 152 | 152 | 53 |
| Unnao | 148 | 148 | 52 |
| Ghaziabad | 145 | 145 | 51 |
| Chitrakoot | 142 | 142 | 50 |
| Bareilly | 139 | 139 | 49 |
| Rampur | 136 | 136 | 48 |
| Gonda | 133 | 133 | 47 |
| Hamirpur | 131 | 131 | 46 |
| Bijnor | 128 | 128 | 45 |
| Baghpat | 126 | 126 | 44 |
| Aligarh | 123 | 123 | 43 |
| Mainpuri | 121 | 121 | 42 |
| Kaushambi | 119 | 119 | 42 |
| Hathras | 117 | 117 | 41 |
| Pilibhit | 115 | 115 | 40 |
| Jhansi | 113 | 113 | 40 |
| Moradabad | 111 | 111 | 39 |
| Bahraich | 109 | 109 | 38 |
| Raebareli | 107 | 107 | 37 |
| Pratapgarh | 105 | 105 | 37 |
| Farrukhabad | 104 | 104 | 36 |
| Lalitpur | 102 | 102 | 36 |
| Kanpur Nagar | 101 | 101 | 35 |
| Varanasi | 99 | 99 | 35 |
| Prayagraj | 98 | 98 | 34 |
| Basti | 96 | 96 | 34 |
| Kannauj | 95 | 95 | 33 |
| Shrawasti | 93 | 93 | 33 |
| Shravasti | 92 | 92 | 32 |
| Kheri | 91 | 91 | 32 |
| Bhadohi | 89 | 89 | 31 |
| Ayodhya | 88 | 88 | 31 |
| Mahoba | 87 | 87 | 30 |
| Kanpur Dehat | 86 | 86 | 30 |
| Lakhimpur Kheri | 85 | 85 | 30 |
| Balrampur | 84 | 84 | 29 |
| Jalaun | 80 | 80 | 28 |
| All districts (79) | 32,357 | 32,357 | 11,325 |
The Beauty Parlors database for Uttar Pradesh, India includes 32,357+ 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 Beauty Parlors database for Uttar Pradesh, India contains 32,357+ 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 Beauty 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 beauty parlors footprint in Uttar Pradesh, India.
Yes. The Beauty 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.
Looking to reach world wide data decision-makers in Uttar Pradesh, India? This database aggregates 32,357+ verified records through the Data2Sales AI engine, pulling from verified public registries, official websites, social profiles, and licensed data partners. Dead numbers, closed storefronts, and duplicates are stripped before export — you receive a clean, CRM-ready CSV.
Last Update:
Aug 03, 2026 08:52 AM
Published:
Jul 06, 2026 04:21 AM
Rows (Regular):
16,179
Rows (Extended):
32,357
Category:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
