Costantin Petrol Station Locations Dataset – Italy
Costantin Petrol Station Locations Dataset – Italy
Costantin is a family-run Italian group based in the Veneto region that has expanded into a significant independent petrol station network. It focuses on regional proximity and high-quality service, often integrating convenience stores and cafés into its locations.
There are 118 Costantin Petrol Stations as of 7 July 2026 in Italy. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Costantin 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: 118 Costantin petrol stations in Italy
- Contents: Coordinates, addresses, postal codes, administrative divisions, and contact details
- 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
- City
- Admin_level_1
- Admin_level_2
- Commune
- Region
- Population
- Postal Code
- Address
- Wheelchair
- Phone
- Website
- Fuel Type
- Opening hours
Data Quality Scorecard
- Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
- Contact Details (Phone)77%
- Web Address75%
- Opening Hours47%
Data Preview: Sample geospatial records from the Costantin dataset in Italy
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 3beb188... | Costantin (Pisona) | 45.293280 | 11.010058 | 37063 | Via Pisona, Pisona, 37063, Provincia ... |
| 48d2fbc... | Costantin | 45.485018 | 10.859361 | 37026 | 1 Via dei Sassi, 37026, Provincia di ... |
| 04cc07a... | Costantin | 44.501150 | 11.490192 | 40055 | 108 Via P. C. S. Nasica, 40055, Città... |
| 89fd825... | Costantin (Pordenone) | 45.984121 | 12.643466 | 33170 | 57/A Via Montereale, Pordenone, 33170... |
| 15cf6b5... | Costantin (Mantova) | 45.176326 | 10.786087 | 46100 | 20 Via Brescia, Mantova, 46100, Provi... |
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 Costantin locations in Italy is found in Veneto (66 sites, equivalent to 1.36 Costantin petrol stations per 100,000 residents). This is followed by Lombardia (19 sites; 0.19 per 100,000) and Piemonte (13 sites; 0.31 per 100,000). From a market-penetration perspective, Veneto has the highest brand density at 1.36 locations per 100,000 people (population: 4,840,000), making it the most saturated region for Costantin in Italy. By contrast, Trentino-Alto Adige records only 0.09 locations per 100,000 residents (population: 1,085,000), 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 Italy
Brand bundle
Top 17 Petrol Stations Brands in Italy - €400
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 Italy - 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 Italy: Map these Costantin locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Italy: Overlay demographic indicators to deeply understand the population structures and household types surrounding these Costantin locations.
- Explore demographics data insights for Italy: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for Italy (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 Italy-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 Italy
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?
- 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.
- CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
- Vendor Distribution: FMCG and wholesale suppliers identifying specific retail locations for direct-store-delivery (DSD) pitching.
- Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
- Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
- 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: Can this dataset be imported into Power BI or Tableau?
A: Yes. The CSV structure is compatible with Power BI, Tableau, Looker Studio, and other business intelligence platforms.
Q: Can this dataset be used for logistics planning?
A: Yes. Many customers use these datasets to optimize delivery territories, distribution networks, route planning, and last-mile logistics analysis.
Q: Can I combine this dataset with administrative boundaries?
A: Yes. The coordinates can be spatially joined with municipalities, census units, postal areas, and other administrative polygons.
Q: What coordinate reference system is used?
A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).
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 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 Costantin dataset to identify underserved regions in Italy for potential market expansion.""Identify municipalities in Italy with strong demographic potential but no nearby Costantin presence.""Analyze geographic gaps in the current Costantin network and identify underserved regions in Italy with strong expansion potential."
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.