All Supermarket Locations in Hungary: Complete Geographic Dataset
SKU: 15628607788

All Supermarket Locations in Hungary: Complete Geographic Dataset

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Description

All Supermarket Locations in Hungary: Complete Geographic DatasetQuick links: Overview Dataset Fields Brand Distribution Distribution by Region Download FAQ Analyze with AI All Supermarkets locations in Hungary complete national dataset This dataset contains a complete, geocoded collection of Supermarkets in Hungary, including branded chains and independent locations. It provides a complete national coverage with 12,179 verified locations suitable for territory planning, market sizing and spatial analysis. Last

All Supermarkets locations in Hungary - complete national dataset

This dataset contains a complete, geocoded collection of Supermarkets in Hungary, including branded chains and independent locations. It provides a complete national coverage with 12,179 verified locations suitable for territory planning, market sizing and spatial analysis.

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

  • Dél-Alföld: 1,736 supermarkets
  • Dél-Dunántúl: 1,344 supermarkets
  • Közép-Dunántúl: 1,480 supermarkets
  • Közép-Magyarország: 2,813 supermarkets
  • Nyugat-Dunántúl: 1,357 supermarkets
  • Észak-Alföld: 1,942 supermarkets
  • Észak-Magyarország: 1,507 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.

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 I request custom enrichment fields?

A: Yes. Custom enrichment services may be available depending on the project scope and geographic coverage requirements.

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: Does the dataset include latitude and longitude coordinates?

A: Yes. Each location record includes precise WGS84 latitude and longitude coordinates for geospatial analysis and mapping workflows.

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: Can I analyze this dataset with AI tools?

A: Yes. The dataset is structured for compatibility with AI workflows including ChatGPT, Claude, Gemini, RAG pipelines, and Python-based analytics.

Q: Can I request the data in GeoJSON or Shapefile format?

A: Yes. Alternative delivery formats such as GeoJSON, Shapefile, Excel, and PostgreSQL imports are available upon request.

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 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 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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SKU: 15628607788

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