migrolino Supermarket Locations Dataset – Switzerland
migrolino Supermarket Locations Dataset – Switzerland
migrolino is a leading Swiss convenience retailer primarily found at Migrol gas stations and major railway hubs. It provides a wide range of fresh, high-quality groceries and ready-to-eat meals for customers with busy lifestyles.
There are 377 migrolino Supermarkets as of 30 May 2026 in Switzerland. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all migrolino 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: 377 migrolino supermarkets in Switzerland
- 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: 30 May 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
- Opening hours
Data Quality Scorecard
- Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
- Contact Details (Phone)90%
- Web Address90%
- Opening Hours90%
- Popularity Score100%
Data Preview: Sample geospatial records from the migrolino dataset in Switzerland
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| b8048e0... | migrolino (Pambio-Noranco) | 45.980745 | 8.928768 | 6915 | 48 Via Pian Scairolo, Pambio-Noranco,... |
| 8af9d91... | migrolino (Bióggio) | 46.017855 | 8.913449 | 6934 | 23 Strada Regina, Bióggio, 6934, Luga... |
| 8566a65... | migrolino (Basel) | 47.571475 | 7.569096 | 4056 | 100 Flughafenstrasse, Basel, 4056, Sw... |
| 95b63c3... | migrolino (Zürich) | 47.420965 | 8.507953 | 8046 | 282 Riedenhaldenstrasse, Zürich, 8046... |
| eb558a1... | migrolino (Chiasso) | 45.821431 | 9.005639 | 6832 | 20 Via Tinelle, Chiasso, 6832, Mendri... |
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 30 May 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 migrolino locations in Switzerland is found in Zürich (77 sites, equivalent to 4.75 migrolino supermarkets per 100,000 residents). This is followed by Ticino (48 sites; 13.52 per 100,000) and Aargau (34 sites; 4.63 per 100,000). From a market-penetration perspective, Ticino has the highest brand density at 13.52 locations per 100,000 people (population: 355,000), making it the most saturated region for migrolino in Switzerland. By contrast, Basel-Stadt records only 1.0 locations per 100,000 residents (population: 200,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Related geospatial datasets
- Administrative boundaries and full polygon dataset for Switzerland: Map these migrolino locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Switzerland: Overlay demographic indicators to deeply understand the population structures and household types surrounding these migrolino locations.
- Explore demographics data insights for Switzerland: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Explore a rich library of Switzerland-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 Switzerland
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?
- CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
- Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
- 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.
- Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
- Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
Frequently Asked Questions
Q: How recent is this dataset?
A: This dataset was last updated on 30 May 2026 and is periodically refreshed through automated collection and validation workflows.
Q: What coordinate reference system is used?
A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).
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: Is this dataset suitable for market analysis?
A: Yes. The dataset is designed for retail analysis, competitor benchmarking, site selection, market coverage studies, and geospatial intelligence workflows.
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.
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 preview the dataset before purchasing?
A: Yes. A free sample is available so you can evaluate the structure, fields, and geospatial quality before purchase.
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 migrolino dataset to identify underserved regions in Switzerland for potential market expansion.""Analyze which migrolino locations in Switzerland are positioned in highly competitive retail zones versus standalone markets.""Analyze geographic gaps in the current migrolino network and identify underserved regions in Switzerland 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.