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Description
Kiwi Supermarket Locations Dataset – NorwayQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Kiwi is a leading Norwegian discount supermarket chain easily recognized by its distinctive green branding and focus on fresh produce. As part of NorgesGruppen, it is a market leader in the price sensitive segment of the grocery industry. There are 730 Kiwi Supermarkets as of 29 May 2026 in Norway. This
Kiwi is a leading Norwegian discount supermarket chain easily recognized by its distinctive green branding and focus on fresh produce. As part of NorgesGruppen, it is a market leader in the price-sensitive segment of the grocery industry.
There are 730 Kiwi Supermarkets as of 29 May 2026 in Norway. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Kiwi 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: 730 Kiwi 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)99%
- Web Address61%
- Opening Hours99%
- Popularity Score100%
Data Preview: Sample geospatial records from the Kiwi dataset in Norway
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 9344eed... | Kiwi (Langestrand) | 59.051355 | 10.022090 | 3264 | 6 Hammergata, 3264, Larvik, Norway |
| 3e4b8ed... | Kiwi (Kleppe) | 58.781478 | 5.618496 | 4351 | 2C Verdalsvegen, 4351, Klepp, Norway |
| 4d272de... | Kiwi (Bjørkelangen) | 59.883759 | 11.570840 | 1940 | 8 Rådhusveien, 1940, Aurskog-Høland, ... |
| 5983ed3... | Kiwi (Grua) | 60.256928 | 10.660332 | 2742 | 6 A Myllavegen, 2742, Lunner, Norway |
| ae2d726... | Kiwi (Rakkestad) | 59.416859 | 11.350253 | 1890 | 1 Sarpsborgveien, 1890, Rakkestad, 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 Kiwi locations in Norway is found in Oslo Og Viken (279 sites, equivalent to 13.48 Kiwi supermarkets per 100,000 residents). This is followed by Vestlandet (192 sites; 13.38 per 100,000) and Agder Og Sør-Østlandet (107 sites; 13.99 per 100,000). From a market-penetration perspective, Innlandet has the highest brand density at 22.63 locations per 100,000 people (population: 380,000), making it the most saturated region for Kiwi in Norway. By contrast, Trøndelag records only 6.12 locations per 100,000 residents (population: 490,000), 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 Kiwi 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 Kiwi 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?
- Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
- Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
- B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
- 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.
- Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
- Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
- Store Closure & Relocation Strategy: Corporate teams optimizing existing footprints by analyzing underperforming regions.
Frequently Asked Questions
Q: What coordinate reference system is used?
A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).
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 I request custom enrichment fields?
A: Yes. Custom enrichment services may be available depending on the project scope and geographic coverage requirements.
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: 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.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this Kiwi dataset to identify underserved regions in Norway for potential market expansion.""Identify regions in Norway where Kiwi has a disproportionately strong or weak presence relative to population density.""Analyze the relationship between Kiwi site distribution and regional economic activity across 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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Exchange/Return Notes
- We offer a 30-day return/exchange service after receiving.
- Final sale items are not eligible for returns or exchanges.
- To process your return/exchange, please contact us at [email protected]
- Please click here for more details>>> Return & Exchange Policy