Classic Petrol Station Locations Dataset – Germany

Classic is a medium-sized German petrol station brand operated by the Lühmann Group, primarily serving the northern and central regions of the country. It focuses on high-quality fuels and reliable local service in both urban and rural settings.

There are 185 Classic Petrol Stations as of 7 July 2026 in Germany. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Classic 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 Classic dataset in Germany

ID	Location Title	Latitude	Longitude	Postal Code	Full Address
64cf626...	Classic Tankstelle (Stammheim)	48.696974	8.775155	75365	2 Hauptstraße, Calw, 75365, Karlsruhe...
d6ff1c2...	Classic Tankstelle (Salzkotten)	51.674130	8.612953	33154	22 Paderborner Straße, Salzkotten, 33...
74f978d...	Classic Tankstelle (Heikendorf)	54.369486	10.201878	24226	1 Dorfstraße, Heikendorf, 24226, Germany
201fc6c...	Classic Tankstelle (Mulsum)	53.670752	8.547642	27639	27 Mulsumer Landstraße, Wurster Nords...
2c7ad52...	Classic Tankstelle (Petershagen)	52.376648	8.955843	32469	33 Meßlinger Straße, Petershagen, 324...

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 Classic locations in Germany is found in Niedersachsen (83 sites, equivalent to 1.03 Classic petrol stations per 100,000 residents). This is followed by Nordrhein-Westfalen (40 sites; 0.22 per 100,000) and Schleswig-Holstein (19 sites; 0.65 per 100,000). From a market-penetration perspective, Niedersachsen has the highest brand density at 1.03 locations per 100,000 people (population: 8,055,000), making it the most saturated region for Classic in Germany. By contrast, Sachsen records only 0.02 locations per 100,000 residents (population: 4,055,000), 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

Related geospatial datasets

• Administrative boundaries and full polygon dataset for Germany: Map these Classic locations against highly precise administrative polygons for territory analysis and spatial structuring.
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• 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?

• Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
• 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.
• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
• 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.
• Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
• CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.

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 Classic dataset to identify underserved regions in Germany for potential market expansion."
• "Identify strategic locations in Germany where new Classic sites could maximize geographic coverage while minimizing overlap."
• "Create a regional ranking of Classic coverage efficiency using population-to-store ratios 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.