List of REMA 1000 Supermarkets in Denmark: 439 Locations (CSV)

List of REMA 1000 Supermarkets in Denmark: 439 Locations (CSV)

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REMA 1000 is a highly successful discount chain originally from Norway that has become one of Denmark's most popular grocery retailers. It operates through a franchise model, emphasizing low prices and high efficiency in neighborhood locations.

As of 7 October 2026, REMA 1000 operates 439 supermarkets in Denmark, according to Geolocet. The most stores are in Region Midtjylland (115), Region Syddanmark (108) and Region Hovedstaden (91). The dataset is a CSV file with 17 fields.

Dataset Summary

  • Dataset Coverage: 439 REMA 1000 supermarkets in Denmark
  • Contents: Coordinates, addresses, postal codes, administrative divisions, contact details, and popularity scores
  • File Format: Fully geocoded CSV dataset (UTF-8)
  • Free Sample: Instantly accessible dataset to verify structure and data quality
  • Use Cases: Suitable for GIS, retail analytics, site selection, and AI/RAG workflows
  • Last Updated: 7 October 2026

Dataset Methodology:

This dataset is compiled from publicly available business listings, official company sources, and geospatial validation workflows. Automated quality checks and manual analyst reviews are applied to improve coordinate precision, address standardisation, duplicate detection, and overall analytical consistency.

It is periodically reviewed and updated to reflect known network changes, closures, relocations, and newly identified locations.

Map showing the geographical distribution of REMA 1000 locations in Denmark

Dataset fields included in the CSV:

  • GUID
  • Title
  • Latitude
  • Longitude
  • Street No
  • Street
  • City
  • Kommune
  • Region
  • Population
  • Postal Code
  • Address
  • Wheelchair
  • Popularity Score
  • Phone
  • Website
  • Opening hours

Data Quality Scorecard

  • Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
  • Contact Details (Phone)90%
  • Web Address90%
  • Opening Hours90%
  • Popularity Score100%

Data Preview: Sample geospatial records from the REMA 1000 dataset in Denmark

ID Location Title Latitude Longitude Postal Code Full Address
28e6304... REMA 1000 (Viborg) 56.460387 9.399258 8800 2 Farvervej, Viborg, 8800, Denmark
9ce748a... REMA 1000 (Esbjerg Ø) 55.477876 8.488620 6705 196 Storegade, Esbjerg, 6705, Denmark
56999cd... REMA 1000 (Hvide Sande) 56.015473 8.126693 6960 65 Parallelvej, Hvide Sande, 6960, De...
23c87cf... REMA 1000 (Allingåbro) 56.466986 10.318891 8961 47B Rougsøvej, Allingåbro, 8961, Denmark
9b69911... REMA 1000 (Slots Bjergby) 55.372712 11.329645 4200 Slots Bjergby, 4200, Denmark

Note: Only a subset of the full dataset fields are displayed here. Download the free sample (option above) to view all fields and verify the data structure.

Why download from Geolocet?

  • Instant download: full dataset available immediately after purchase, no waiting, no manual fulfilment
  • Free sample first: verify structure, fields, and coordinate precision before you commit
  • Analysis-ready CSV: clean, standardised, and compatible with Excel, Python, QGIS, Power BI, and PostgreSQL out of the box
  • Regularly updated: last updated 7 October 2026

✅ Data looks right? Add to cart ↑ or download the free sample first.

Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of REMA 1000 locations in Denmark is found in Region Midtjylland (115 sites, equivalent to 8.32 REMA 1000 supermarkets per 100,000 residents). This is followed by Region Syddanmark (108 sites; 8.69 per 100,000) and Region Hovedstaden (91 sites; 4.68 per 100,000). From a market-penetration perspective, Region Nordjylland has the highest brand density at 8.77 locations per 100,000 people (population: 590,000), making it the most saturated region for REMA 1000 in Denmark. By contrast, Region Hovedstaden records only 4.68 locations per 100,000 residents (population: 1,940,000), indicating a potential white-space opportunity for network expansion or competitor analysis. This granular regional data helps analysts understand specific market density, localized brand presence, and population-adjusted coverage across Denmark.

Region REMA 1000 Locations Population Density per 100,000
Region Midtjylland 115 1,380,000 8.32
Region Syddanmark 108 1,240,000 8.69
Region Hovedstaden 91 1,940,000 4.68
Region Sjælland 73 855,000 8.51
Region Nordjylland 52 590,000 8.77

Geolocet is a store location data provider. See also our POI datasets.

Also available for Denmark

Brand bundle

Top 12 Supermarket Brands in Denmark: 2,448 Locations

All major chains in one standardised dataset. Best for competitive benchmarking, network analysis, and market sizing across the leading brands.

View the Top 12 Supermarket Brands dataset →

Full market coverage

Denmark Supermarket POI Dataset: 5,385 Locations

Includes everything in the brand bundle plus independent operators, smaller chains, and local businesses not covered by the top brands. Best for full market mapping, territory planning, and white-space analysis.

View the Denmark Supermarket POI dataset →

Need the data in another format?

We can deliver this dataset in alternative formats upon request (GeoJSON, Shapefile, Excel, PostgreSQL import files, etc.). Contact us at contact@geolocet.com.

Who uses this data?

  • Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
  • Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
  • Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
  • Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
  • Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
  • B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
  • CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.

Frequently Asked Questions

Q: How many REMA 1000 supermarkets are there in each Region of Denmark?

A: Region Midtjylland has 115 REMA 1000 supermarkets (8.32 stores per 100,000 residents), Region Syddanmark 108 (8.69 stores per 100,000 residents) and Region Hovedstaden 91 (4.68 stores per 100,000 residents). Region Sjælland has 73 (8.51 stores per 100,000 residents) and Region Nordjylland 52 (8.77 stores per 100,000 residents).

Q: Which fields does the dataset include, and how complete are they?

A: The dataset has 17 fields. GUID, Title, Latitude, Longitude, City, Kommune, Region, Population, Postal Code, Address and Popularity Score are present in 100% of records; Street No and Street are 96.6%, Wheelchair 98.9%, Phone 89.5%, Website 90.0% and Opening hours 89.7%.

Q: When was the data last updated?

A: The data was last updated on 7 October 2026.

Q: Under which licence can I use the data?

A: The data is provided under the Geolocet terms of use: https://geolocet.com/pages/terms-of-use.

Q: In which format is the data delivered?

A: The data is delivered as a CSV file.

Analyze this data with AI

Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:

  • "Analyze this REMA 1000 dataset to identify underserved regions in Denmark for potential market expansion."
  • "Assess how effectively the current REMA 1000 network covers major commercial and residential hubs across Denmark."
  • "Detect clusters where REMA 1000 sites are in close proximity to analyze potential self-cannibalization in Denmark."

Disclaimer: All brand logos and trademarks displayed are the property of their respective owners and are used strictly for identification purposes. This product consists of geospatial location data only; no images, logos, or trademark rights are included in the downloadable files.