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Description
Coop Supermarket Locations Dataset – NorwayQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Coop Norge is a consumer owned cooperative that manages several retail banners including Coop Mega, Coop Prix, and Coop Obs. It is one of the dominant forces in the Norwegian market, emphasizing member benefits and community ownership. There are 563 Coop Supermarkets as of 29 May 2026 in Norway. This dataset
Coop Norge is a consumer-owned cooperative that manages several retail banners including Coop Mega, Coop Prix, and Coop Obs. It is one of the dominant forces in the Norwegian market, emphasizing member benefits and community ownership.
There are 563 Coop Supermarkets as of 29 May 2026 in Norway. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Coop 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: 563 Coop supermarkets in Norway
- Contents: Coordinates, addresses, postal codes, administrative divisions, contact details, and popularity scores
- 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: 29 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
- Town
- Admin_level_1
- Admin_level_2
- Municipality
- Region
- Population
- Postal Code
- Address
- Wheelchair
- Popularity Score
- Phone
- Website
- Opening hours
Data Quality Scorecard
- Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
- Contact Details (Phone)96%
- Web Address95%
- Opening Hours96%
- Popularity Score100%
Data Preview: Sample geospatial records from the Coop dataset in Norway
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 897aa11... | Matkroken Trones (Trones) | 64.741935 | 12.843876 | 7892 | 4 Furuveien, 7892, Namsskogan, Norway |
| e1eb175... | Coop Marked (Inderøy) | 63.911854 | 11.190747 | 7670 | 1 Buavegen, 7670, Inderøy, Norway |
| 553118b... | Matkroken Lurøy (Lurøy) | 66.398344 | 12.850619 | 8766 | 1C Jektvikveien, 8766, Lurøy, Norway |
| 83148f3... | Coop Prix (Longva) | 62.671933 | 6.270892 | 6293 | 2 Kvernhusvegen, 6293, Haram, Norway |
| f49b2bb... | Coop Marked (Vassenden) | 61.492498 | 6.112385 | 6847 | 885 Jølstravegen, 6847, Sunnfjord, No... |
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 29 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 Coop locations in Norway is found in Vestlandet (156 sites, equivalent to 10.87 Coop supermarkets per 100,000 residents). This is followed by Nord-Norge (125 sites; 25.51 per 100,000) and Trøndelag (97 sites; 19.8 per 100,000). From a market-penetration perspective, Nord-Norge has the highest brand density at 25.51 locations per 100,000 people (population: 490,000), making it the most saturated region for Coop in Norway. By contrast, Oslo Og Viken records only 4.15 locations per 100,000 residents (population: 2,070,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Also available for Norway
Brand bundle
Top 9 Grocery Brands in Norway - €240
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 Norway - 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 Norway: Map these Coop locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Norway: Overlay demographic indicators to deeply understand the population structures and household types surrounding these Coop locations.
- Explore demographics data insights for Norway: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Explore a rich library of Norway-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 Norway
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?
- Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
- Vendor Distribution: FMCG and wholesale suppliers identifying specific retail locations for direct-store-delivery (DSD) pitching.
- Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
- Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
- Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
- Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
- Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
Frequently Asked Questions
Q: Are postal codes included for all locations?
A: Postal codes are included wherever available and validated as part of the standardization workflow.
Q: Is the dataset standardized for analytics workflows?
A: Yes. Address formatting, administrative areas, and geospatial fields are standardized to improve consistency across analytical environments.
Q: Is this dataset useful for accessibility studies?
A: Yes. Analysts can combine the coordinates with mobility, transport, and demographics datasets to evaluate accessibility and service coverage.
Q: Can I request the data in GeoJSON or Shapefile format?
A: Yes. Alternative delivery formats such as GeoJSON, Shapefile, Excel, and PostgreSQL imports are available upon request.
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 be used for logistics planning?
A: Yes. Many customers use these datasets to optimize delivery territories, distribution networks, route planning, and last-mile logistics analysis.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this Coop dataset to identify underserved regions in Norway for potential market expansion.""Calculate the total population coverage for Coop in Norway using a 10km catchment radius around each coordinate.""Analyze proximity between Coop locations and major highways, ring roads, or arterial transport corridors in Norway."
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.
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