Coop DagliBrugsen Supermarket Locations Dataset – Denmark

Coop DagliBrugsen Supermarket Locations Dataset – DenmarkQuick links: Dataset Summary Methodology Download Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI DagliBrugsen stores are smaller, local grocery outlets designed to meet the daily needs of residents in rural areas and small towns. They prioritize convenience and community involvement, providing a reliable local supply chain across Denmark. There are 130 Coop DagliBrugsen Supermarkets as of 28 May 2026 in Denmark. This

DagliBrugsen stores are smaller, local grocery outlets designed to meet the daily needs of residents in rural areas and small towns. They prioritize convenience and community involvement, providing a reliable local supply chain across Denmark.

There are 130 Coop DagliBrugsen 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 DagliBrugsen 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 DagliBrugsen dataset in Denmark

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of Coop DagliBrugsen locations in Denmark is found in Region Syddanmark (41 sites, equivalent to 3.31 Coop DagliBrugsen supermarkets per 100,000 residents). This is followed by Region Midtjylland (32 sites; 2.32 per 100,000) and Region Sjælland (28 sites; 3.27 per 100,000). From a market-penetration perspective, Region Syddanmark has the highest brand density at 3.31 locations per 100,000 people (population: 1,240,000), making it the most saturated region for Coop DagliBrugsen in Denmark. By contrast, Region Hovedstaden records only 0.67 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 DagliBrugsen 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 DagliBrugsen 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 [email protected].

Who uses this data?

• CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
• Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
• Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
• Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
• Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
• Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
• Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.

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 DagliBrugsen dataset to identify underserved regions in Denmark for potential market expansion."
• "Analyze which Coop DagliBrugsen locations in Denmark are positioned in highly competitive retail zones versus standalone markets."
• "Identify strategic locations in Denmark where new Coop DagliBrugsen sites could maximize geographic coverage while minimizing overlap."

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.