GLOBUS Supermarket Locations Dataset – Germany
GLOBUS Supermarket Locations Dataset – Germany
GLOBUS is a large hypermarket chain in Germany characterized by its in-house production, including professional butcher shops and bakeries. It provides a massive assortment of food and non-food items in very large retail formats.
There are 85 GLOBUS Supermarkets as of 27 May 2026 in Germany. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all GLOBUS 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: 85 GLOBUS supermarkets in Germany
- 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: 27 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
- Area
- City
- Admin_level_1
- Admin_level_2
- Gemainde
- Federal State
- Population
- Postal Code
- Address
- Wheelchair
- Popularity Score
- Phone
- Website
- Opening hours
Data Quality Scorecard
- Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
- Contact Details (Phone)84%
- Web Address79%
- Opening Hours84%
- Popularity Score100%
Data Preview: Sample geospatial records from the GLOBUS dataset in Germany
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 34caaa4... | GLOBUS (Bauschheim) | 49.967048 | 8.389552 | 65428 | 1 Am Steinmarkt, Rüsselsheim am Main,... |
| 91f62de... | GLOBUS (Sankt Tönis) | 51.316441 | 6.473844 | 47918 | 19 Höhenhöfe, Tönisvorst, 47918, Düss... |
| c8bf38a... | GLOBUS (Dutenhofen) | 50.561068 | 8.608072 | 35582 | 2 Industriestraße, Wetzlar, 35582, Gi... |
| 0c68819... | GLOBUS (Altmühldorf) | 48.250094 | 12.495040 | 84453 | 18 Siemensstraße, Mühldorf am Inn, 84... |
| a44cfb3... | GLOBUS (Linderbach) | 50.976173 | 11.105874 | 99098 | 117 Weimarische Straße, Erfurt, 99098... |
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 27 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 GLOBUS locations in Germany is found in Rheinland-Pfalz (19 sites, equivalent to 0.46 GLOBUS supermarkets per 100,000 residents). This is followed by Saarland (11 sites; 1.12 per 100,000) and Bayern (10 sites; 0.08 per 100,000). From a market-penetration perspective, Saarland has the highest brand density at 1.12 locations per 100,000 people (population: 985,000), making it the most saturated region for GLOBUS in Germany. By contrast, Niedersachsen records only 0.02 locations per 100,000 residents (population: 8,055,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Learn more about the brand network in our report: View Report
Also available for Germany
Brand bundle
Top 27 Grocery Brands in Germany - €480
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 Germany - 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 Germany: Map these GLOBUS locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Germany: Overlay demographic indicators to deeply understand the population structures and household types surrounding these GLOBUS locations.
- Explore demographics data insights for Germany: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for Germany (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.
- Explore a rich library of Germany-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 Germany
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?
- B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
- Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
- Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
- 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.
- Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
- Store Closure & Relocation Strategy: Corporate teams optimizing existing footprints by analyzing underperforming regions.
- Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
Frequently Asked Questions
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: 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 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: Is the dataset immediately downloadable after purchase?
A: Yes. The full dataset becomes available for instant digital download immediately after purchase.
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 used for academic or research purposes?
A: Yes. Researchers and universities frequently use these datasets for urban studies, geography, economics, and spatial analytics projects.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this GLOBUS dataset to identify underserved regions in Germany for potential market expansion.""Measure average inter-store distance between GLOBUS locations across different regions of Germany.""Analyze the relationship between GLOBUS site distribution and regional economic activity across Germany."
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.