This dataset covers 337 verified records spread across
33+ cities in Uttar Pradesh.
337 records carry a verified phone number and
61 include a business website — directly usable for
outreach, segmentation, and CRM import.
The highest-density cities are
Agra (78 listings), Meerut (55 listings), Prayagraj (37 listings), Lucknow (36 listings), Ghaziabad (30 listings), Kanpur (24 listings), Varanasi (20 listings), and Allahabad (20 listings).
The Nursing Homes database for Uttar Pradesh, India includes 337+ 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.
Aishwarya (IN) bought 1 week ago
·Vicky (IN) bought 1 week ago
·Sweta (IN) bought 1 week ago
·Aarti (IN) bought 1 week ago
·Gajendra (IN) bought 1 week ago
How to use this data
Investor diligence — scope the nursing homes TAM in Uttar Pradesh, India from a verified count not a marketing estimate.
Sizing + segmentation — slice the nursing homes universe in Uttar Pradesh, India by region, city size and Google rating tier.
Sales coaching — review actual nursing homes call-quality across territories in Uttar Pradesh, India.
Frequently asked about this dataset
How many businesses are in the Nursing Homes database for Uttar Pradesh, India?
The Nursing Homes database for Uttar Pradesh, India contains 337+ verified businesses as of 2026, each with phone, email, address, website and GPS coordinates. The full record count is shown on this page above.
Where can I download a Nursing Homes database for Uttar Pradesh, India?
The complete Nursing Homes 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.
What fields are included in the Nursing Homes dataset?
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.
How accurate is the Nursing Homes data for Uttar Pradesh, India?
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 nursing homes footprint in Uttar Pradesh, India.
Is the Nursing Homes dataset updated regularly?
Yes. The Nursing Homes 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.
Can I use the Nursing Homes data for marketing and outreach?
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.
What format do I receive the Nursing Homes database in?
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.
How quickly can I download the dataset after purchase?
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.
About the Nursing Homes Database in Uttar Pradesh, India
Looking to reach world wide data decision-makers in Uttar Pradesh, India? This database aggregates 337+ 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.
Also available — Zone-wide roll-ups
Buy multiple neighbouring states in a single file. Cheaper than the country pack, wider than any one state.