REMA 1000 Supermarket Locations Dataset – Denmark
REMA 1000 Supermarket Locations Dataset – Denmark
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.
There are 431 REMA 1000 Supermarkets as of 28 May 2026 in Denmark. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all REMA 1000 locations, including full address details, administrative divisions, and precise WGS84 latitude/longitude coordinates - structured for GIS, retail analytics, mapping, and AI/RAG workflows.
Dataset Summary
- Dataset Coverage: 431 REMA 1000 supermarkets in Denmark
- Contents: Coordinates, addresses, postal codes, and administrative divisions
- 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: 28 May 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.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- City
- Kommune
- Region
- Population
- Postal Code
- Address
- Wheelchair
Data Preview: Sample geospatial records from the REMA 1000 dataset in Denmark
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 15a1c06... | REMA 1000 (Hobro) | 56.641253 | 9.795649 | 9500 | 1 Brogade, Hobro, 9500, Denmark |
| 6553fb4... | REMA 1000 (Skanderborg) | 56.039169 | 9.914827 | 8660 | 31 Vroldvej, Skanderborg, 8660, Denmark |
| 941b1dc... | REMA 1000 (Høje Taastrup) | 55.647618 | 12.270675 | 2630 | 41 Høje Taastrup Boulevard, Høje Taas... |
| 493a798... | REMA 1000 (Svendborg) | 55.064228 | 10.592251 | 5700 | 100 A Vestergade, Svendborg, 5700, De... |
| baf9e11... | REMA 1000 (Vildbjerg) | 56.201931 | 8.767962 | 7480 | 12 Industrivej, Vildbjerg, 7480, 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 28 May 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 (114 sites, equivalent to 8.26 REMA 1000 supermarkets per 100,000 residents). This is followed by Region Syddanmark (103 sites; 8.31 per 100,000) and Region Hovedstaden (91 sites; 4.69 per 100,000). From a market-penetration perspective, Region Nordjylland has the highest brand density at 8.81 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 4.69 locations per 100,000 residents (population: 1,940,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Also available for Denmark
Brand bundle
Top 12 Grocery Brands in Denmark - €244
All major chains in one standardised dataset. Best for competitive benchmarking, network analysis, and market sizing across the leading brands.
View Top Brands dataset →Full market coverage
All Grocery Locations in Denmark - complete POI dataset
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 full POI dataset →Related geospatial datasets
- Administrative boundaries and full polygon dataset for Denmark: Map these REMA 1000 locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Denmark: Overlay demographic indicators to deeply understand the population structures and household types surrounding these REMA 1000 locations.
- Explore demographics data insights for Denmark: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for Denmark (small-area income analysis): Download an analysis-ready dataset on income distribution across small geographic units - ideal for segmentation, customer analytics, location planning, and socio-economic scoring.
- Income distribution and socio-economic patterns in Denmark - expert analysis: A detailed blog post explaining income geography, disparities, and how income-based indicators can support location intelligence and market analytics.
- Explore a rich library of Denmark-specific datasets on our dedicated country page: detailed demographics, wealth indicators, multi-level boundaries, and a broad spectrum of retail POIs. View demographics, retail POI, and administrative boundary datasets for Denmark
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: What coordinate reference system is used?
A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).
Q: Are postal codes included for all locations?
A: Postal codes are included wherever available and validated as part of the standardization workflow.
Q: Can I request custom enrichment fields?
A: Yes. Custom enrichment services may be available depending on the project scope and geographic coverage requirements.
Q: Does the dataset contain duplicate locations?
A: Duplicate detection and validation workflows are applied during processing to improve consistency and reduce redundant records.
Q: How accurate are the coordinates?
A: Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.
Q: Is this dataset useful for accessibility studies?
A: Yes. Analysts can combine the coordinates with mobility, transport, and demographics datasets to evaluate accessibility and service coverage.
Q: Is the dataset standardized for analytics workflows?
A: Yes. Address formatting, administrative areas, and geospatial fields are standardized to improve consistency across analytical environments.
Q: Does the dataset include unique identifiers?
A: Yes. Each record includes a GUID field to support deduplication, joins, and downstream database operations.
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.