MOL Petrol Station Locations Dataset – Poland
MOL Petrol Station Locations Dataset – Poland
MOL entered Poland in a major way by acquiring a significant portion of the Lotos station network. The Hungarian giant is currently rebranding these sites to the MOL name, introducing its "Fresh Corner" cafe concept.
There are 365 MOL Petrol Stations as of 7 July 2026 in Poland. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all MOL 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: 365 MOL petrol stations in Poland
- 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
- Latitude
- Longitude
- Street No
- Street
- City
- Admin_level_1
- Admin_level_2
- Municipality
- Region
- 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)65%
- Web Address65%
- Opening Hours67%
Data Preview: Sample geospatial records from the MOL dataset in Poland
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 95e15b3... | MOL (Skorupy) | 53.123530 | 23.217054 | 15-501 | 121A Baranowicka, Białystok, 15-501, ... |
| 36c87e7... | MOL (Psie Pole) | 51.130494 | 17.037598 | 50-231 | 39 Trzebnicka, Wrocław, 50-231, Powia... |
| 5e907c0... | MOL (Cieszyn) | 49.764392 | 18.636770 | 43-400 | 45 Katowicka, Cieszyn, 43-400, Powiat... |
| c22cb57... | MOL (Obozisko) | 51.415199 | 21.154267 | 26-600 | 14 Warszawska, Radom, 26-600, Powiat ... |
| 70f7a31... | MOL (Dębno Polskie) | 51.580936 | 16.845480 | 63-900 | Dębno Polskie, 63-900, Powiat rawicki... |
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 MOL locations in Poland is found in Mazowieckie (46 sites, equivalent to 0.84 MOL petrol stations per 100,000 residents). This is followed by Wielkopolskie (39 sites; 1.12 per 100,000) and Pomorskie (34 sites; 1.44 per 100,000). From a market-penetration perspective, Podlaskie has the highest brand density at 1.93 locations per 100,000 people (population: 1,140,000), making it the most saturated region for MOL in Poland. By contrast, Podkarpackie records only 0.44 locations per 100,000 residents (population: 2,060,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Also available for Poland
Brand bundle
Top 9 Petrol Stations Brands in Poland - €264
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 Poland - 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 Poland: Map these MOL locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Poland: Overlay demographic indicators to deeply understand the population structures and household types surrounding these MOL locations.
- Explore demographics data insights for Poland: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for Poland (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 Poland-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 Poland
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?
- Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
- Vendor Distribution: FMCG and wholesale suppliers identifying specific retail locations for direct-store-delivery (DSD) pitching.
- CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
- Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
- Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
- Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
- Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
- Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
Frequently Asked Questions
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 analyze this dataset with AI tools?
A: Yes. The dataset is structured for compatibility with AI workflows including ChatGPT, Claude, Gemini, RAG pipelines, and Python-based analytics.
Q: How accurate are the coordinates?
A: Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.
Q: Are phone numbers and websites included?
A: Yes. Where available, the dataset includes standardized phone numbers and official website URLs.
Q: Is the dataset immediately downloadable after purchase?
A: Yes. The full dataset becomes available for instant digital download immediately after purchase.
Q: Does the dataset include all locations in the country?
A: The dataset is designed to provide a complete and standardized list of known MOL locations operating in Poland as of 7 July 2026.
Q: Can this dataset support expansion planning?
A: Yes. Analysts often use the dataset to identify underserved areas, evaluate regional density, and support retail expansion decisions.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this MOL dataset to identify underserved regions in Poland for potential market expansion.""Map the concentration of MOL locations relative to major retail centers and shopping districts in Poland.""Analyze the clustering behavior of MOL locations to determine whether the network prioritizes convenience, coverage, or saturation strategies."
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.