Kvickly Supermarket Locations Dataset – Denmark

Kvickly Supermarket Locations Dataset – Denmark

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Kvickly operates as a hypermarket chain under Coop Danmark, providing an extensive selection of both food items and non-food merchandise like home decor and clothing. It is one of the oldest and most established large-scale retail brands in the country.

There are 61 Kvickly Supermarkets as of 28 May 2026 in Denmark. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Kvickly 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: 61 Kvickly 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 Kvickly 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 Kvickly dataset in Denmark

ID Location Title Latitude Longitude Postal Code Full Address
e9cc23a... Kvickly (Rønne) 55.101722 14.692778 3700 28 Nordre Kystvej, Rønne, 3700, Denmark
777cd5d... Kvickly (Risskov) 56.189121 10.214860 8240 5 Frijsenborgvej, Risskov, 8240, Denmark
2992c84... Kvickly (Stenløse) 55.767871 12.195496 3660 1 Centertorvet, Stenløse, 3660, Denmark
efc6dd0... Kvickly (Grindsted) 55.759175 8.922371 7200 34 Vestergade, Grindsted, 7200, Denmark
df916de... Kvickly (København S) 55.664179 12.622976 2300 43 Strandlodsvej, København, 2300, De...

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 Kvickly locations in Denmark is found in Region Hovedstaden (20 sites, equivalent to 1.03 Kvickly supermarkets per 100,000 residents). This is followed by Region Midtjylland (16 sites; 1.16 per 100,000) and Region Syddanmark (13 sites; 1.05 per 100,000). From a market-penetration perspective, Region Midtjylland has the highest brand density at 1.16 locations per 100,000 people (population: 1,380,000), making it the most saturated region for Kvickly in Denmark. By contrast, Region Nordjylland records only 0.68 locations per 100,000 residents (population: 590,000), 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.
  • 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.
  • Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
  • Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.

Frequently Asked Questions

Q: Are the datasets suitable for machine learning workflows?

A: Yes. The structured tabular format and standardized coordinates make the datasets suitable for machine learning and predictive analytics applications.

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 opening hours?

A: Yes, opening hours are included where publicly available and validated during the data standardization process.

Q: Can this dataset be imported into Power BI or Tableau?

A: Yes. The CSV structure is compatible with Power BI, Tableau, Looker Studio, and other business intelligence platforms.

Analyze this data with AI

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

  • "Analyze this Kvickly dataset to identify underserved regions in Denmark for potential market expansion."
  • "Identify fast-growing suburban areas in Denmark that currently have limited access to nearby supermarkets."
  • "Evaluate how evenly Kvickly locations are distributed across provinces, districts, or municipalities 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.