Coop Brugsen Supermarket Locations Dataset – Denmark

Coop Brugsen is a community-focused supermarket chain that emphasizes local presence and quality everyday groceries. It operates as part of the consumer-owned Coop Amba, often serving as a central shopping point for local neighborhoods.

There are 135 Coop Brugsen Supermarkets as of 28 May 2026 in Denmark. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Coop Brugsen locations, including full address details, administrative divisions, and precise WGS84 latitude/longitude coordinates - structured for GIS, retail analytics, mapping, and AI/RAG workflows.

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.

Data Preview: Sample geospatial records from the Coop Brugsen dataset in Denmark

ID	Location Title	Latitude	Longitude	Postal Code	Full Address
f433a8a...	Brugsen	55.465689	10.020991	5463	63 Rugårdsvej, Harndrup, 5463, Denmark
0098d62...	Brugsen	55.125439	11.951393	4720	50 Næstvedvej, Bårse, 4720, Denmark
d99f3e1...	Brugsen	56.026147	8.393126	6940	100 Bredgade, Lem, 6940, Denmark
44c11a9...	Brugsen	55.815276	10.638158	8305	12 Havnevej, Samsø, 8305, Denmark
9ebc41a...	Brugsen	55.872155	9.612692	8763	5-7 Gl Jernbanevej, Rask Mølle, 8763,...

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.

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of Coop Brugsen locations in Denmark is found in Region Midtjylland (41 sites, equivalent to 2.97 Coop Brugsen supermarkets per 100,000 residents). This is followed by Region Syddanmark (31 sites; 2.5 per 100,000) and Region Sjælland (27 sites; 3.16 per 100,000). From a market-penetration perspective, Region Sjælland has the highest brand density at 3.16 locations per 100,000 people (population: 855,000), making it the most saturated region for Coop Brugsen in Denmark. By contrast, Region Hovedstaden records only 0.93 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

Related geospatial datasets

• Administrative boundaries and full polygon dataset for Denmark: Map these Coop Brugsen 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 Coop Brugsen 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?

• CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
• Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
• Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
• Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
• Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
• Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.

Frequently Asked Questions

Analyze this data with AI

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

• "Analyze this Coop Brugsen dataset to identify underserved regions in Denmark for potential market expansion."
• "Create a regional ranking of Coop Brugsen coverage efficiency using population-to-store ratios across Denmark."
• "Calculate the total population coverage for Coop Brugsen in Denmark using a 10km catchment radius around each coordinate."

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.