METRO Supermarket Locations Dataset – Germany

METRO Supermarket Locations Dataset – GermanyQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI METRO is a leading international wholesale company in Germany, catering primarily to the hotel, restaurant, and catering (HoReCa) industry. While it requires a trade membership, it is a massive player in the food distribution landscape. There are 95 METRO Supermarkets as of 27 May 2026 in Germany. This

METRO is a leading international wholesale company in Germany, catering primarily to the hotel, restaurant, and catering (HoReCa) industry. While it requires a trade membership, it is a massive player in the food distribution landscape.

There are 95 METRO Supermarkets as of 27 May 2026 in Germany. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all METRO locations, including full address details, administrative divisions, and precise WGS84 latitude/longitude coordinates - structured for GIS, retail analytics, mapping, and AI/RAG workflows.

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.

Data Quality Scorecard

Data Preview: Sample geospatial records from the METRO dataset in Germany

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.

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of METRO locations in Germany is found in Nordrhein-Westfalen (16 sites, equivalent to 0.09 METRO supermarkets per 100,000 residents). This is followed by Baden-Württemberg (14 sites; 0.13 per 100,000) and Niedersachsen (14 sites; 0.17 per 100,000). From a market-penetration perspective, Mecklenburg-Vorpommern has the highest brand density at 0.25 locations per 100,000 people (population: 1,615,000), making it the most saturated region for METRO in Germany. By contrast, Schleswig-Holstein records only 0.07 locations per 100,000 residents (population: 2,930,000), 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

Related geospatial datasets

• Administrative boundaries and full polygon dataset for Germany: Map these METRO 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 METRO 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 [email protected].

Who uses this data?

• 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.
• Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
• 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.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
• 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

Analyze this data with AI

Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:

• "Analyze this METRO dataset to identify underserved regions in Germany for potential market expansion."
• "Analyze proximity between METRO locations and major highways, ring roads, or arterial transport corridors in Germany."
• "Identify fast-growing suburban areas in Germany that currently have limited access to nearby supermarkets."

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.