føtex Supermarket Locations Dataset – Denmark

føtex Supermarket Locations Dataset – Denmark

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føtex is a large-format supermarket and department store chain owned by the Salling Group, offering a mix of groceries, electronics, and textiles. It is recognized for its high-quality bakeries and consistent focus on value for money.

There are 116 føtex Supermarkets as of 28 May 2026 in Denmark. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all føtex 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: 116 føtex 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.

Map showing the geographical distribution of føtex locations in Denmark

Dataset fields included in the CSV:

  • GUID
  • Title
  • Latitude
  • Longitude
  • Street No
  • Street
  • City
  • Kommune
  • Region
  • Population
  • Postal Code
  • Address
  • Wheelchair

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 føtex locations in Denmark is found in Region Hovedstaden (49 sites, equivalent to 2.53 føtex supermarkets per 100,000 residents). This is followed by Region Syddanmark (24 sites; 1.94 per 100,000) and Region Midtjylland (23 sites; 1.67 per 100,000). From a market-penetration perspective, Region Hovedstaden has the highest brand density at 2.53 locations per 100,000 people (population: 1,940,000), making it the most saturated region for føtex in Denmark. By contrast, Region Sjælland records only 1.17 locations per 100,000 residents (population: 855,000), 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 →

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?

  • Vendor Distribution: FMCG and wholesale suppliers identifying specific retail locations for direct-store-delivery (DSD) pitching.
  • 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.
  • Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
  • 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.
  • Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.

Frequently Asked Questions

Q: How recent is this dataset?

A: This dataset was last updated on 28 May 2026 and is periodically refreshed through automated collection and validation workflows.

Q: Can I combine this dataset with administrative boundaries?

A: Yes. The coordinates can be spatially joined with municipalities, census units, postal areas, and other administrative polygons.

Q: What coordinate reference system is used?

A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).

Q: How accurate are the coordinates?

A: Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.

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: Does the dataset include latitude and longitude coordinates?

A: Yes. Each location record includes precise WGS84 latitude and longitude coordinates for geospatial analysis and mapping workflows.

Q: Can I use this dataset in GIS software?

A: Yes. The dataset is suitable for GIS platforms including QGIS, ArcGIS, GeoPandas, CARTO, and other spatial analysis environments.

Q: Can I use this dataset for proximity analysis?

A: Yes. The geocoded coordinates are suitable for drive-time analysis, catchment modeling, nearest-neighbor analysis, and accessibility studies.

Analyze this data with AI

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

  • "Analyze this føtex dataset to identify underserved regions in Denmark for potential market expansion."
  • "Map the concentration of føtex locations relative to major retail centers and shopping districts in Denmark."
  • "Cross-reference these supermarkets with urban transit data to score each location's accessibility for non-driving customers."

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.