SKU: 94234225599

France Grocery Locations Dataset – Top 19 Supermarket Brands

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Description

France Grocery Locations Dataset – Top 19 Supermarket BrandsQuick links: Overview Dataset Fields Brand Distribution Distribution by Region Download FAQ Analyze with AI Top 19 Supermarket Chains Across France: Premium Multi Brand Location Dataset Unlock a complete, ready to use dataset featuring the leading Supermarket brands in France. This expertly compiled Top Brands dataset consolidates all major Supermarket chains in France, delivering a clean, standardised and analysis ready collection of 27,836

Top 19 Supermarket Chains Across France: Premium Multi-Brand Location Dataset

Unlock a complete, ready-to-use dataset featuring the leading Supermarket brands in France. This expertly compiled Top Brands dataset consolidates all major Supermarket chains in France, delivering a clean, standardised and analysis-ready collection of 27,836 locations. Perfect for businesses seeking high-quality data for market sizing, competitive landscape analysis, network optimisation, and strategic planning.

Last updated: 27 May 2026.

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
  • Popularity Score
  • Phone
  • Website
  • Opening hours

Brand distribution

Supermarkets distribution by Region

  • Pop - Corse: 3,196,773 supermarkets
  • Île-De-France: 4,865 supermarkets
  • Auvergne-Rhône-Alpes: 3,834 supermarkets
  • Occitanie: 3,017 supermarkets
  • Nouvelle-Aquitaine: 2,771 supermarkets
  • Provence-Alpes-Côte D'Azur: 2,482 supermarkets
  • Hauts-De-France: 2,220 supermarkets
  • Grand Est: 1,876 supermarkets
  • Normandie: 1,584 supermarkets
  • Bretagne: 1,389 supermarkets
  • Pays De La Loire: 1,356 supermarkets
  • Bourgogne-Franche-Comté: 1,210 supermarkets
  • Centre-Val De Loire: 968 supermarkets
  • Corse: 260 supermarkets

Direct access after purchase of the complete locations dataset for France

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: What coordinate reference system is used?

A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).

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 use this dataset for competitor benchmarking?

A: Yes. The dataset is frequently used to compare retail footprints, market density, and regional presence against competing brands.

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 this data be combined with demographics datasets?

A: Yes. Many customers combine these locations with demographics, income, mobility, and administrative boundary datasets for deeper spatial 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.

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.

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 France for potential market expansion."
  • "Cross-reference these supermarkets with urban transit data to score each location's accessibility for non-driving customers."
  • "Assess the accessibility of this multi-brand locations in France based on proximity to population centers and public infrastructure."
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SKU: 94234225599

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Grantham, US
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