SPAR Supermarket Locations Dataset – Denmark
SPAR Supermarket Locations Dataset – Denmark
SPAR Denmark consists of independently owned neighborhood stores that are part of the global SPAR network and managed locally by Dagrofa. These stores focus on providing fresh, local products and essential services to their respective communities.
There are 149 SPAR Supermarkets as of 28 May 2026 in Denmark. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all SPAR 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: 149 SPAR 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.
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 SPAR dataset in Denmark
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 6b5f59a... | SPAR (Tønder) | 54.939144 | 8.873033 | 6270 | 1 Kongevej, Tønder, 6270, Denmark |
| f93df25... | SPAR (Hjørring) | 57.471914 | 9.797224 | 9800 | 82 Strandvejen, Hjørring, 9800, Denmark |
| 6de6d4e... | SPAR (Ejstrupholm) | 55.983184 | 9.285251 | 7361 | 33 Søndergade, Ejstrupholm, 7361, Den... |
| a161f34... | SPAR (Stenløse) | 55.791289 | 12.263773 | 3660 | Stenløse, 3660, Denmark |
| e070131... | SPAR (Frederiksværk) | 56.017087 | 12.046810 | 3300 | 155 Helsingevej, Frederiksværk, 3300,... |
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 SPAR locations in Denmark is found in Region Nordjylland (47 sites, equivalent to 7.97 SPAR supermarkets per 100,000 residents). This is followed by Region Syddanmark (40 sites; 3.23 per 100,000) and Region Midtjylland (31 sites; 2.25 per 100,000). From a market-penetration perspective, Region Nordjylland has the highest brand density at 7.97 locations per 100,000 people (population: 590,000), making it the most saturated region for SPAR in Denmark. By contrast, Region Hovedstaden records only 0.98 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
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 →Related geospatial datasets
- Administrative boundaries and full polygon dataset for Denmark: Map these SPAR 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 SPAR 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?
- Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
- Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
- Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
- Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
- Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
- Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
- B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
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 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: Does the dataset include unique identifiers?
A: Yes. Each record includes a GUID field to support deduplication, joins, and downstream database operations.
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.
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: Can this dataset support expansion planning?
A: Yes. Analysts often use the dataset to identify underserved areas, evaluate regional density, and support retail expansion decisions.
Q: Are postal codes included for all locations?
A: Postal codes are included wherever available and validated as part of the standardization workflow.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this SPAR dataset to identify underserved regions in Denmark for potential market expansion.""Identify SPAR sites with large footprints in Denmark that are optimal candidates for EV charging infrastructure overlays.""Analyze proximity between SPAR locations and major highways, ring roads, or arterial transport corridors 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.