Rude Health Retailers
Worldwide: 3 countries (0 US) · 1,153 locations
1,153 stores that carry Rude Health (0 in the US): every store on Rude Health's own store locator on rudehealth.com.
More about this list
Name, address, phone, website and the locator's own store details.
The file has all 1,153 locations in one download. Building the same list by searching one area at a time tends to miss places, and a missed place looks like a gap in coverage that is not really there.
Need just some of them? Ask in your own words.
●Where the rows are
≡Sample Data Preview
| store name | address | city | state | zip | phone | website | brand | store id | phone source | website source | status | directions url | brand locator store id | brand locator url | country as published | updated date | src priority | place from map point | is chain | chain name | chain store count | overture place id | overture name | overture category | overture brand | overture match meters | naics code | naics title | sic code | sic title | industry source | geo precision | address quality | country | latitude | longitude | source | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Morrisons | Vulcan Road | Minehead, Somerset | TA24 6DG | +441643704477 | https://groceries.morrisons.com/search?entry=Rude%20Health&filters=rude-health-159459 | Rude Health | u9601-7082248 | Overture Maps place | Brand store locator | Listed | https://www.google.com/maps/dir/?api=1&destination=51.20417839,-3.46514568 | 7082248 | https://rudehealth.com/pages/store-locator | United Kingdom | 2026-10-16 | 0 | Y | Morrisons | 1405 | 95fe9f14-ef6a-46b3-86ad-d61bd9fbe92f | Morrisons | grocery_store | McColl's | 58 | 445110 | Supermarkets and Other Grocery Retailers (except Convenience Retailers) | 5411 | Grocery Stores | Overture category of the matched place | source | no_house_number | GB | 51.20417839 | -3.46514568 | Rude Health store locator | |||
| Co-Op | Station Road | Buntingford | SG9 9HT | https://www.coop.co.uk | Rude Health | u9601-7843068 | Brand store locator | Listed | https://www.google.com/maps/dir/?api=1&destination=51.94381322,-0.01669235 | 7843068 | https://rudehealth.com/pages/store-locator | Hertfordshire | 2026-10-16 | 0 | Y | Y | Co-Op | 2853 | source | no_house_number | GB | 51.94381322 | -0.01669235 | Rude Health store locator | ||||||||||||||
| Co-Op | 110 High Street | Heathfield | TN21 8JD | https://www.coop.co.uk | Rude Health | u9601-7843106 | Brand store locator | Listed | https://www.google.com/maps/dir/?api=1&destination=50.9700659,0.2471216 | 7843106 | https://rudehealth.com/pages/store-locator | East Sussex | 2026-10-16 | 0 | Y | Y | Co-Op | 2853 | source | missing_city_or_zip | GB | 50.9700659 | 0.2471216 | Rude Health store locator | ||||||||||||||
| Co-Op | 162 Worcester Road | Malvern | WR14 1AA | https://www.coop.co.uk | Rude Health | u9601-7843171 | Brand store locator | Listed | https://www.google.com/maps/dir/?api=1&destination=52.12814854,-2.31393379 | 7843171 | https://rudehealth.com/pages/store-locator | Worcestershire | 2026-10-16 | 0 | Y | Y | Co-Op | 2853 | source | missing_city_or_zip | GB | 52.12814854 | -2.31393379 | Rude Health store locator | ||||||||||||||
| Co-Op | 12 Bradford Street | Shifnal | TF11 8AT | https://www.coop.co.uk | Rude Health | u9601-7843152 | Brand store locator | Listed | https://www.google.com/maps/dir/?api=1&destination=52.66672869,-2.37270949 | 7843152 | https://rudehealth.com/pages/store-locator | Shropshire | 2026-10-16 | 0 | Y | Y | Co-Op | 2853 | source | missing_city_or_zip | GB | 52.66672869 | -2.37270949 | Rude Health store locator |
{}What's in each row
| Field | What it is | Rows filled |
|---|---|---|
| brand | The brand whose store locator lists the store | 100% |
| store | Store id (unique per place in this file) | 100% |
| store | Store name as the brand's locator lists it | 100% |
| address | Street address | 100% |
| city | City | 40% |
| state | State or province code (US always; outside the US where the locator gives one) | 30% |
| zip | ZIP or postal code | 70% |
| country | Two-letter country code | 100% |
| latitude | Latitude | 100% |
| longitude | Longitude | 100% |
| phone | Store phone | 30% |
| phone | Where the phone came from: the brand's store locator, or the matched Overture place | 30% |
| website | Store website | 100% |
| website | Where the website came from: the brand's store locator, or the matched Overture place | 100% |
| status | Listed | 100% |
| directions | Google Maps directions link | 100% |
| brand | The store's id on the brand's locator | 100% |
| brand | The brand's store locator page | 100% |
| country | The country as the locator wrote it, where it differs from the code | 99% |
| source | Source of the row | 100% |
| updated | Date the brand's locator was read | 100% |
| src_ | Another field the brand's locator publishes for the store: priority | 100% |
| place | Y when the locator gave no country or state and they were set from the store's map point | 31% |
| is | Y when 5 or more stores in these brand lists carry the same store name | 100% |
| chain | Chain name | 100% |
| chain | Stores with that chain name across these brand lists | 100% |
| overture | Overture Maps place id of the matched place (join key to Overture data) | 31% |
| overture | Name of the matched Overture place | 31% |
| overture | Overture category of the matched place | 31% |
| overture | Brand of the matched Overture place | 28% |
| overture | Distance between the store and the matched Overture place, in metres | 31% |
| naics | NAICS 2022 code | 28% |
| naics | NAICS title | 28% |
| sic | SIC code | 28% |
| sic | SIC title | 28% |
| industry | Where the industry code came from | 28% |
| geo_ | How the map point was set | 100% |
| address_ | complete, no house number, po box, missing city or zip or missing | 100% |
Rows filled is measured on every row of the delivered file.
✓Where this data comes from
Each row names the public source it came from, so any record can be checked against where it was published.
October 16, 2026
Snapshot built
39 fields
Columns in the file
Fill measured
On every row of the delivered file
How we build and date every file: methodology.
Using ChatGPT, Claude or an API?
No setup needed. Ask ChatGPT or Claude your question about the Rude Health Retailers and give it this page: it can open https://locationlists.com/find?dataset=rude-health-retailers with the filters you need and show you the count and price.
Using ChatGPT or Claude? Tell it to answer from locationlists.com/find — no account, no connector.
How assistants ask
No connector needed. Any AI assistant can answer from this site with a web link, no connector, no account: open https://locationlists.com/find with the question as query parameters.
If a question needs filtering, distance, drive time, combining lists or a price, open a /find link: either put the question itself in q=, or build the structured link. The answer does not need an API, a connector or an account.
Simplest, the question itself: https://locationlists.com/find?q=<the question in plain words>
Or set the parts yourself: https://locationlists.com/find?dataset=<slug>&state=<ST>&city=<city>&county=<county>&zip=<zip>&near=<place or zip>&radius=<miles>&drive=<minutes>&where=<column>:<op>:<value>&total=<rows>
Leave out what the question does not need. Use radius for straight-line miles or drive for minutes of driving (5 to 60), not both; near can name several places separated by | to reach from any of them. To ask about several lists at once, use datasets with two or more names, or category with a kind of business. To compare two lists, add relate=nearest and the other list with b. in front of its parameters. To count by area, use areas=county (or zip, state, metro). To keep only places whose county, ZIP code, metro area or state meets a Census figure, add area_where (for example county:population>1000000); with areas, per=100000 gives counts per 100,000 residents.
Links an assistant can open, each showing how many rows match, a few preview rows and the price for just that part:
- Only rows where isChain is Y: https://locationlists.com/find?dataset=rude-health-retailers&where=isChain%3Aeq%3AY
- The whole list: add a city, state, ZIP code or distance:
https://locationlists.com/find?dataset=rude-health-retailers
Optional: connect for repeat use or wallet payments:
Read https://locationlists.com/skill.md and follow the instructions to connect LocationLists. Then show me the Rude Health Retailers list.Your assistant will walk you through setup and show you the price before you pay.
For developers
At 1,153 records this dataset is not sold by the row — buy the file. Without a connector, open https://locationlists.com/find?dataset=rude-health-retailers. An agent connected to https://locationlists.com/mcp can still search it, read a free sample file of up to 10 rows and buy the whole file itself. How agent purchasing works
?Frequently Asked Questions
Where does this data come from?
From Rude Health's own store locator on rudehealth.com. We read every store on its map on 2026-10-16. A store the map shows twice (same name and address) is one row.
What is one row?
One store on the brand's locator, with the brand's own tags for it (storeType) and any custom fields the locator shows.
Does it include stores outside the US?
Yes. 1,153 of the 1,153 stores are outside the US, across 3 countries. Filter on country for one market.
Where do websites and phones come from?
From the brand's locator where it gives them. Otherwise from the Overture Maps place at the same spot with the same name. phoneSource and websiteSource say which.
How complete are phones and websites?
346 of the 1,153 stores have a phone, and 1,150 of the 1,153 have a website.