JET Petrol Station Locations Dataset – Germany
JET Petrol Station Locations Dataset – Germany
JET is a highly popular petrol station brand in Germany owned by Phillips 66, consistently winning awards for its customer service and pricing. It focuses on a streamlined, efficient fueling experience and is often cited as the country's most popular petrol station chain.
There are 749 JET 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 JET 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: 749 JET petrol stations 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: 7 July 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
- Group
- 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
- Fuel Type
- Opening hours
Data Quality Scorecard
- Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
- Contact Details (Phone)93%
- Web Address90%
- Opening Hours92%
- Popularity Score100%
Data Preview: Sample geospatial records from the JET dataset in Germany
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| a205139... | JET (Neckarstadt-West) | 49.509140 | 8.467536 | 68169 | 83 Untermühlaustraße, Mannheim, 68169... |
| f7916ca... | JET Tankstelle (Aschersleben) | 51.766598 | 11.480325 | 06449 | 18 C Güstener Straße, Aschersleben, 0... |
| 5ba85e2... | JET (Kulmbach) | 50.112746 | 11.451197 | 95326 | 8 Albert-Ruckdeschel-Straße, Kulmbach... |
| 5796eaa... | JET Tankstelle (Rathenow) | 52.583918 | 12.337153 | 14712 | 8B Milower Landstraße, Rathenow, 1471... |
| d71d6d6... | JET Tankstelle (Grünberg) | 50.593795 | 8.956232 | 35305 | 17-19 Gießener Straße, Grünberg, 3530... |
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 7 July 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 JET locations in Germany is found in Nordrhein-Westfalen (183 sites, equivalent to 1.02 JET petrol stations per 100,000 residents). This is followed by Bayern (134 sites; 1.01 per 100,000) and Baden-Württemberg (109 sites; 0.98 per 100,000). From a market-penetration perspective, Bremen has the highest brand density at 1.19 locations per 100,000 people (population: 675,000), making it the most saturated region for JET in Germany. By contrast, Berlin records only 0.51 locations per 100,000 residents (population: 3,690,000), 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 16 Petrol Stations 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 Petrol Stations 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 JET 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 JET 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?
- 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.
- Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
- Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
- Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
- 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.
Frequently Asked Questions
Q: Does the dataset include all locations in the country?
A: The dataset is designed to provide a complete and standardized list of known JET locations operating in Germany as of 7 July 2026.
Q: Are phone numbers and websites included?
A: Yes. Where available, the dataset includes standardized phone numbers and official website URLs.
Q: Does the dataset include accessibility-related attributes?
A: Yes. Certain datasets include accessibility-related indicators such as wheelchair accessibility where publicly available.
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.
Q: Is this dataset useful for accessibility studies?
A: Yes. Analysts can combine the coordinates with mobility, transport, and demographics datasets to evaluate accessibility and service coverage.
Q: Can I integrate this dataset into a PostgreSQL/PostGIS database?
A: Yes. The dataset structure is compatible with PostgreSQL/PostGIS and other relational spatial databases.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this JET dataset to identify underserved regions in Germany for potential market expansion.""Calculate the total population coverage for JET in Germany using a 10km catchment radius around each coordinate.""Assess the accessibility of JET locations in Germany based on proximity to population centers and public infrastructure."
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.