TinQ Petrol Station Locations Dataset – Netherlands
TinQ Petrol Station Locations Dataset – Netherlands
TinQ is a leading Dutch unmanned petrol station chain owned by Enviem, known for its bright orange branding and aggressive pricing. It focuses on offering a quick and efficient self-service experience at numerous locations across the Netherlands.
There are 435 TinQ Petrol Stations as of 7 July 2026 in the Netherlands. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all TinQ 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: 435 TinQ petrol stations in the Netherlands
- 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
- Settlement
- Region
- Population
- Postal Code
- Address
- Popularity Score
- Phone
- Website
- Opening hours
Data Quality Scorecard
- Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
- Contact Details (Phone)93%
- Web Address97%
- Opening Hours96%
- Popularity Score100%
Data Preview: Sample geospatial records from the TinQ dataset in Netherlands
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| f75a8ff... | TinQ (Heerde) | 52.399342 | 6.046760 | 8181 BG | 13-15 Europaweg, Heerde, 8181 BG, Hee... |
| e7448e9... | TinQ (Zutphen) | 52.136442 | 6.203084 | 7204 SB | 7 Emmerikseweg, Zutphen, 7204 SB, Zut... |
| b5d0e33... | TinQ (Breda) | 51.601994 | 4.776643 | 4825 BA | 10 Crogtdijk, Breda, 4825 BA, Breda, ... |
| cff7c17... | TinQ (Arnhem) | 52.001744 | 5.905397 | 6815 GD | 2 Eduard van Beinumlaan, Arnhem, 6815... |
| 2d08ad5... | TinQ (Terschuur) | 52.163156 | 5.516053 | 3784 WK | 154 Hoevelakenseweg, Terschuur, 3784 ... |
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 TinQ locations in the Netherlands is found in Gelderland (84 sites, equivalent to 3.89 TinQ petrol stations per 100,000 residents). This is followed by Noord-Brabant (59 sites; 2.22 per 100,000) and Noord-Holland (52 sites; 1.74 per 100,000). From a market-penetration perspective, Drenthe has the highest brand density at 5.54 locations per 100,000 people (population: 505,000), making it the most saturated region for TinQ in the Netherlands. By contrast, Zuid-Holland records only 1.01 locations per 100,000 residents (population: 3,860,000), 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 the Netherlands
Brand bundle
Top 14 Petrol Stations Brands in the Netherlands - €360
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 the Netherlands - 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 the Netherlands: Map these TinQ locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for the Netherlands: Overlay demographic indicators to deeply understand the population structures and household types surrounding these TinQ locations.
- Explore demographics data insights for the Netherlands: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for the Netherlands (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.
- Income distribution and socio-economic patterns in the Netherlands - expert analysis: A detailed blog post explaining income geography, disparities, and how income-based indicators can support location intelligence and market analytics.
- Explore a rich library of the Netherlands-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 the Netherlands
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?
- 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.
- 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.
- Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
- Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
- B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
- CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
Frequently Asked Questions
Q: What coordinate reference system is used?
A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).
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: How accurate are the coordinates?
A: Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.
Q: Are the datasets suitable for machine learning workflows?
A: Yes. The structured tabular format and standardized coordinates make the datasets suitable for machine learning and predictive analytics applications.
Q: How recent is this dataset?
A: This dataset was last updated on 7 July 2026 and is periodically refreshed through automated collection and validation workflows.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this TinQ dataset to identify underserved regions in the Netherlands for potential market expansion.""Identify the most central TinQ locations in the Netherlands to serve as hubs for a last-mile delivery network.""Compare the spatial distribution of TinQ locations against major competitor clusters to identify overlap and whitespace opportunities in the Netherlands."
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.