REWE Supermarket Locations Dataset – Germany

REWE Supermarket Locations Dataset – GermanyQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI REWE is one of Germanys leading retail groups, operating a vast network of supermarkets known for quality and innovation. It pioneered the large scale adoption of pick up services and delivery in the German grocery market. There are 5,014 REWE Supermarkets as of 27 May 2026 in Germany. This dataset is

REWE is one of Germany’s leading retail groups, operating a vast network of supermarkets known for quality and innovation. It pioneered the large-scale adoption of pick-up services and delivery in the German grocery market.

There are 5,014 REWE Supermarkets as of 27 May 2026 in Germany. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all REWE 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 REWE dataset in Germany

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of REWE locations in Germany is found in Nordrhein-Westfalen (1079 sites, equivalent to 6.0 REWE supermarkets per 100,000 residents). This is followed by Bayern (822 sites; 6.21 per 100,000) and Hessen (603 sites; 9.54 per 100,000). From a market-penetration perspective, Hessen has the highest brand density at 9.54 locations per 100,000 people (population: 6,320,000), making it the most saturated region for REWE in Germany. By contrast, Sachsen-Anhalt records only 4.05 locations per 100,000 residents (population: 2,175,000), 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 REWE 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 REWE 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?

• B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
• Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
• Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
• Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
• 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.

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 REWE dataset to identify underserved regions in Germany for potential market expansion."
• "Analyze proximity between REWE locations and major highways, ring roads, or arterial transport corridors in Germany."
• "Generate regional density heatmaps showing where REWE has the strongest and weakest retail presence in 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.