Nahkauf Supermarket Locations Dataset – Germany

Nahkauf Supermarket Locations Dataset – GermanyQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Nahkauf is a proximity store banner operated by the REWE Group, specifically designed to provide grocery supplies in rural areas and small urban neighborhoods. These stores are typically run by independent merchants under the REWE umbrella. There are 547 Nahkauf Supermarkets as of 27 May 2026 in Germany. This

Nahkauf is a proximity store banner operated by the REWE Group, specifically designed to provide grocery supplies in rural areas and small urban neighborhoods. These stores are typically run by independent merchants under the REWE umbrella.

There are 547 Nahkauf Supermarkets as of 27 May 2026 in Germany. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Nahkauf 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 Nahkauf dataset in Germany

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of Nahkauf locations in Germany is found in Hessen (106 sites, equivalent to 1.68 Nahkauf supermarkets per 100,000 residents). This is followed by Baden-Württemberg (72 sites; 0.64 per 100,000) and Bayern (61 sites; 0.46 per 100,000). From a market-penetration perspective, Thüringen has the highest brand density at 2.36 locations per 100,000 people (population: 2,115,000), making it the most saturated region for Nahkauf in Germany. By contrast, Bremen records only 0.15 locations per 100,000 residents (population: 675,000), 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 Nahkauf 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 Nahkauf 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).
• Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
• Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
• Store Closure & Relocation Strategy: Corporate teams optimizing existing footprints by analyzing underperforming regions.
• Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
• Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.

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 Nahkauf dataset to identify underserved regions in Germany for potential market expansion."
• "Analyze geographic gaps in the current Nahkauf network and identify underserved regions in Germany with strong expansion potential."
• "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.