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This dataset covers 1,736 verified records spread across 12+ districts in Himachal Pradesh. 1,736 records carry a verified phone number and 608 include a business website — directly usable for outreach, segmentation, and CRM import.
The highest-density districts are Chamba (559 listings), Sirmaur (280 listings), Lahaul and Spiti (186 listings), Shimla (140 listings), Mandi (112 listings), Hamirpur (93 listings), Bilaspur (80 listings), and Una (70 listings).
Additional coverage spans Solan (62), Kullu (56), Kangra (51), Kinnaur (47) .
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Chamba | 559 | 559 | 196 |
| Sirmaur | 280 | 280 | 98 |
| Lahaul and Spiti | 186 | 186 | 65 |
| Shimla | 140 | 140 | 49 |
| Mandi | 112 | 112 | 39 |
| Hamirpur | 93 | 93 | 33 |
| Bilaspur | 80 | 80 | 28 |
| Una | 70 | 70 | 25 |
| Solan | 62 | 62 | 22 |
| Kullu | 56 | 56 | 20 |
| All districts (12) | 1,736 | 1,736 | 608 |
| Districts | Total | With mobile | With website |
|---|---|---|---|
| Chamba | 559 | 559 | 196 |
| Sirmaur | 280 | 280 | 98 |
| Lahaul and Spiti | 186 | 186 | 65 |
| Shimla | 140 | 140 | 49 |
| Mandi | 112 | 112 | 39 |
| Hamirpur | 93 | 93 | 33 |
| Bilaspur | 80 | 80 | 28 |
| Una | 70 | 70 | 25 |
| Solan | 62 | 62 | 22 |
| Kullu | 56 | 56 | 20 |
| Kangra | 51 | 51 | 18 |
| Kinnaur | 47 | 47 | 16 |
| All districts (12) | 1,736 | 1,736 | 608 |
The Furniture stores database includes 1,736+ verified Furniture stores in Himachal 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.
There are roughly 1,736+ Furniture stores in Himachal Pradesh, India as of 2026. The full list is available as a CSV download on this page with name, address, phone, hours and GPS coordinates for every location.
Right on this page — click Buy / Add to Cart and you'll receive a Data2Sales AI-verified Furniture stores CSV covering all of Himachal Pradesh, India within seconds. Every row is human-checked.
Each Furniture record carries the full operational profile: Furniture 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.
We verify each Furniture entry against the brand's official locator, Google Places and our directory partners on a 30-day cycle. Anything closed or with a dead phone gets dropped before export, so the CSV is the live Himachal Pradesh, India footprint, not last year's.
Yes. The Furniture 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 Furniture 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 Furniture stores — not a stale snapshot. You also get 7 days of unlimited re-downloads from a secure link sent to your email.
The World Wide Data Database for Himachal Pradesh, India is a 1,736+ 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:
Jul 07, 2026 03:00 AM
Published:
May 11, 2026 02:23 AM
Rows (Regular):
781
Rows (Extended):
1,736
Category:
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Roll-up datasets — broader coverage at a higher tier are highlighted below.
