SKU: 34566772531

7-Eleven Supermarket Locations Dataset – Denmark

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Description

7-Eleven Supermarket Locations Dataset – DenmarkQuick links: Dataset Summary Methodology Download Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI 7 Eleven in Denmark is operated by Reitan Retail and serves as a leading convenience retailer found at high traffic urban locations and transport hubs. It offers a wide range of ready to eat meals, snacks, and traditional convenience products tailored to the Danish market. There are 152 7 Eleven Supermarkets as of 28 May

7-Eleven in Denmark is operated by Reitan Retail and serves as a leading convenience retailer found at high-traffic urban locations and transport hubs. It offers a wide range of ready-to-eat meals, snacks, and traditional convenience products tailored to the Danish market.

There are 152 7-Eleven Supermarkets as of 28 May 2026 in Denmark. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all 7-Eleven 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: 152 7-Eleven 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 7-Eleven dataset in Denmark

ID Location Title Latitude Longitude Postal Code Full Address
aa7b999... 7-Eleven (Søborg) 55.747070 12.494526 2860 270 Buddingevej, Søborg, 2860, Denmark
e61b315... 7-Eleven (Esbjerg) 55.487078 8.449181 6700 206 Stormgade, Esbjerg, 6700, Denmark
5f794ed... 7-Eleven (København S) 55.663937 12.601220 2300 43 Amagerbrogade, København, 2300, De...
597c70c... 7-Eleven (Nørrebro) 55.697595 12.544143 2200 190 Nørrebrogade, København, 2200, De...
f80c1cf... 7-Eleven (Hvidovre) 55.648770 12.470361 2650 30 Kettegård Alle, Hvidovre, 2650, 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 7-Eleven locations in Denmark is found in Region Hovedstaden (74 sites, equivalent to 3.81 7-Eleven supermarkets per 100,000 residents). This is followed by Region Syddanmark (24 sites; 1.94 per 100,000) and Region Sjælland (23 sites; 2.69 per 100,000). From a market-penetration perspective, Region Hovedstaden has the highest brand density at 3.81 locations per 100,000 people (population: 1,940,000), making it the most saturated region for 7-Eleven in Denmark. By contrast, Region Midtjylland records only 1.45 locations per 100,000 residents (population: 1,380,000), 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 [email protected].

Who uses this data?

  • Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
  • Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
  • Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
  • Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
  • Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
  • Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
  • Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
  • B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
  • Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.

Frequently Asked Questions

Q: What file format is included with the download?

A: The dataset is delivered as a CSV file compatible with Excel, Python, R, QGIS, Power BI, Tableau, PostgreSQL, and most GIS or analytics platforms.

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: 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: 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 integrate this dataset into a PostgreSQL/PostGIS database?

A: Yes. The dataset structure is compatible with PostgreSQL/PostGIS and other relational spatial databases.

Q: Can I use this dataset for competitor benchmarking?

A: Yes. The dataset is frequently used to compare retail footprints, market density, and regional presence against competing brands.

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 7-Eleven dataset to identify underserved regions in Denmark for potential market expansion."
  • "Analyze the clustering behavior of 7-Eleven locations to determine whether the network prioritizes convenience, coverage, or saturation strategies."
  • "Evaluate how evenly 7-Eleven 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.

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SKU: 34566772531

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lucaberta
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As an admirer of the work that Dan Sullivan and Benjamin Hardy have done individually, I was sure that a collaboration, two “whos” getting together, would be a good hit. And a good it it is! The issue with these kind of books is what happens immediately after one has finished reading them. The issue is to put things into practice, and change the way we do things. This requires thinking, and thinking is hard, and in most cases we do NOT dedicate time to thinking, so the concepts slide into the past, and no change happens. Time for me, and everyone, to change this default state. This review is just the start of a written reflection, a “thinking on paper” exercise, like my friend and great thinker Jean Moroney calls it. For me, it’s time to shift to my journal. For you, dear readers, it’s time to get this book and read it. Make Dan and Ben your “whos”. Now.
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Denisse Villar
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henry Mos
Waukegan, US
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