Meny Supermarket Locations Dataset – Denmark

Meny Supermarket Locations Dataset – Denmark

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Meny is a high-end supermarket chain in Denmark managed by Dagrofa, focusing on premium food experiences and expert service. The stores emphasize fresh fish, meat, and deli departments to attract food enthusiasts and quality-conscious shoppers.

There are 118 Meny Supermarkets as of 28 May 2026 in Denmark. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Meny 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: 118 Meny 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 Meny locations in Denmark

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 Meny dataset in Denmark

ID Location Title Latitude Longitude Postal Code Full Address
fe3afc1... Meny (Præstø) 55.121926 12.038694 4720 9 Svend Gønges Torv, Præstø, 4720, De...
c797949... Meny (Bogense) 55.564350 10.086889 5400 2 Vestre Engvej, Bogense, 5400, Denmark
266f391... Meny (Aarup) 55.379662 10.047961 5560 42 Bredgade, Aarup, 5560, Denmark
cd3c948... Meny (Roslev) 56.701024 8.989693 7870 2 Sallingsundvej, Roslev, 7870, Denmark
69f8616... Meny (Maribo) 54.775842 11.496389 4930 19 Brovejen, Maribo, 4930, 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 Meny locations in Denmark is found in Region Hovedstaden (34 sites, equivalent to 1.75 Meny supermarkets per 100,000 residents). This is followed by Region Midtjylland (22 sites; 1.59 per 100,000) and Region Nordjylland (22 sites; 3.73 per 100,000). From a market-penetration perspective, Region Nordjylland has the highest brand density at 3.73 locations per 100,000 people (population: 590,000), making it the most saturated region for Meny in Denmark. By contrast, Region Syddanmark records only 1.45 locations per 100,000 residents (population: 1,240,000), 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?

  • Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
  • Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
  • Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
  • Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
  • Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
  • Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.

Frequently Asked Questions

Q: Does the dataset include administrative regions?

A: Yes. Administrative fields such as province, district, municipality, postal code, and city are included where available.

Q: Can this dataset support territory optimization?

A: Yes. The dataset is suitable for defining service territories, balancing regional coverage, and optimizing operational footprints.

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 this dataset be used for academic or research purposes?

A: Yes. Researchers and universities frequently use these datasets for urban studies, geography, economics, and spatial analytics projects.

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.

Analyze this data with AI

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

  • "Analyze this Meny dataset to identify underserved regions in Denmark for potential market expansion."
  • "Identify regions in Denmark where Meny has a disproportionately strong or weak presence relative to population density."
  • "Compare the spatial distribution of Meny locations against major competitor clusters to identify overlap and whitespace opportunities 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.