OMV Petrol Station Locations Dataset – Austria
OMV Petrol Station Locations Dataset – Austria
OMV is Austria's leading integrated oil, gas, and petrochemical company, headquartered in Vienna. Its premium petrol stations offer high-quality fuels, VIVA convenience stores, and car wash services throughout the country.
There are 243 OMV Petrol Stations as of 9 July 2026 in Austria. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all OMV 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: 243 OMV petrol stations in Austria
- 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: 9 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
- City
- Admin_level_1
- Admin_level_2
- Gemeinde
- Region
- Population
- Postal Code
- Address
- Wheelchair
- Popularity Score
- Phone
- Website
- Opening hours
Data Quality Scorecard
- Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
- Contact Details (Phone)91%
- Web Address95%
- Opening Hours94%
- Popularity Score100%
Data Preview: Sample geospatial records from the OMV dataset in Austria
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 4567fe9... | OMV (Gries am Brenner) | 47.017720 | 11.507315 | 6156 | 231 Brennersee, Gries am Brenner, 615... |
| f8cb6b2... | OMV (Wiener Neudorf) | 48.077666 | 16.323398 | 2351 | Objekt 9 IZ NÖ-Süd Straße 4, Wiener N... |
| d4411e2... | OMV (Zistersdorf) | 48.542320 | 16.764422 | 2225 | 28a Umfahrungsstraße, Zistersdorf, 22... |
| 07b5d17... | OMV | 47.205449 | 15.315726 | 8121 | 8121, Graz-Umgebung, Austria |
| 0236d62... | OMV (Liebenau) | 47.042141 | 15.464346 | 8041 | 10 Ostbahnstraße, Graz, 8041, Graz, A... |
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 9 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 OMV locations in Austria is found in Niederösterreich (49 sites, equivalent to 2.84 OMV petrol stations per 100,000 residents). This is followed by Tirol (42 sites; 5.42 per 100,000) and Steiermark (30 sites; 2.36 per 100,000). From a market-penetration perspective, Tirol has the highest brand density at 5.42 locations per 100,000 people (population: 775,000), making it the most saturated region for OMV in Austria. By contrast, Wien records only 1.04 locations per 100,000 residents (population: 2,025,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Also available for Austria
Brand bundle
Top 11 Petrol Stations Brands in Austria - €280
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 Austria - 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 Austria: Map these OMV locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Austria: Overlay demographic indicators to deeply understand the population structures and household types surrounding these OMV locations.
- Explore demographics data insights for Austria: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Explore a rich library of Austria-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 Austria
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?
- Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
- Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
- Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
- Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
- 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.
- Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
- Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
Frequently Asked Questions
Q: Is the dataset standardized for analytics workflows?
A: Yes. Address formatting, administrative areas, and geospatial fields are standardized to improve consistency across analytical environments.
Q: Is this dataset useful for franchise analysis?
A: Yes. The dataset can support franchise territory planning, network expansion analysis, and regional performance benchmarking.
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.
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: Does the dataset contain duplicate locations?
A: Duplicate detection and validation workflows are applied during processing to improve consistency and reduce redundant records.
Q: Does the dataset include administrative regions?
A: Yes. Administrative fields such as province, district, municipality, postal code, and city are included where available.
Q: Can I use this dataset in GIS software?
A: Yes. The dataset is suitable for GIS platforms including QGIS, ArcGIS, GeoPandas, CARTO, and other spatial analysis environments.
Q: Can I request custom enrichment fields?
A: Yes. Custom enrichment services may be available depending on the project scope and geographic coverage requirements.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this OMV dataset to identify underserved regions in Austria for potential market expansion.""Evaluate how evenly OMV locations are distributed across provinces, districts, or municipalities in Austria.""Measure average inter-store distance between OMV locations across different regions of Austria."
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.