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Description
Hungary Grocery Locations Dataset – Top 8 Supermarket BrandsQuick links: Overview Dataset Fields Brand Distribution Distribution by Region Download FAQ Analyze with AI Top 8 Supermarket Chains Across Hungary: Premium Multi Brand Location Dataset Unlock a complete, ready to use dataset featuring the leading Supermarket brands in Hungary. This expertly compiled Top Brands dataset consolidates all major Supermarket chains in Hungary, delivering a clean, standardised and analysis ready collection of 3,355
Top 8 Supermarket Chains Across Hungary: Premium Multi-Brand Location Dataset
Unlock a complete, ready-to-use dataset featuring the leading Supermarket brands in Hungary. This expertly compiled Top Brands dataset consolidates all major Supermarket chains in Hungary, delivering a clean, standardised and analysis-ready collection of 3,355 locations. Perfect for businesses seeking high-quality data for market sizing, competitive landscape analysis, network optimisation, and strategic planning.
Last updated: 29 May 2026.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- City
- Municipality
- Region
- Population
- Postal Code
- Address
- Wheelchair
- Popularity Score
- Phone
- Website
- Opening hours
Brand distribution
- ALDI – 190 locations in Hungary
- Auchan – 27 locations in Hungary
- Coop – 1,648 locations in Hungary
- Lidl – 226 locations in Hungary
- PENNY – 251 locations in Hungary
- SPAR – 658 locations in Hungary
- Tesco – 253 locations in Hungary
- Tom Market – 102 locations in Hungary
Supermarkets distribution by Region
- Közép-Magyarország: 750 supermarkets
- Észak-Magyarország: 487 supermarkets
- Észak-Alföld: 465 supermarkets
- Dél-Dunántúl: 444 supermarkets
- Nyugat-Dunántúl: 432 supermarkets
- Közép-Dunántúl: 404 supermarkets
- Dél-Alföld: 373 supermarkets
Direct access after purchase of the complete locations dataset for Hungary
Download the dataset immediately in a clean, analysis-ready CSV format. Ideal for geospatial analysis, competitor benchmarking, market studies, site planning, and retail location intelligence workflows.
Evaluate the dataset before purchase
A free sample is available for download, allowing you to inspect the structure, fields, and geospatial precision before purchasing the full dataset.
Related geospatial datasets
- Administrative boundaries and full polygon dataset for Hungary: Map these supermarkets locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Hungary: Overlay demographic indicators to deeply understand the population structures and household types surrounding these supermarkets locations.
- Explore demographics data insights for Hungary: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for Hungary (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 Hungary - 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 Hungary-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 Hungary
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 [email protected].
Frequently Asked Questions
Q: Can this dataset support territory optimization?
A: Yes. The dataset is suitable for defining service territories, balancing regional coverage, and optimizing operational footprints.
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: Can this dataset be used for academic or research purposes?
A: Yes. Researchers and universities frequently use these datasets for urban studies, geography, economics, and spatial analytics projects.
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 I use this dataset for proximity analysis?
A: Yes. The geocoded coordinates are suitable for drive-time analysis, catchment modeling, nearest-neighbor analysis, and accessibility studies.
Q: How are addresses standardized?
A: Addresses are cleaned and normalized through automated formatting and validation workflows to improve consistency and usability.
Q: How recent is this dataset?
A: This dataset was last updated on May 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 this multi-brand dataset to identify underserved regions in Hungary for potential market expansion.""Analyze proximity between this multi-brand locations and major highways, ring roads, or arterial transport corridors in Hungary.""Identify municipalities in Hungary with strong demographic potential but no nearby this multi-brand presence."
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