SKU: 24897064412

Supermarché Match Supermarket Locations Dataset – France

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Description

Supermarché Match Supermarket Locations Dataset – FranceQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Supermarch Match is a supermarket chain operating primarily in the north and east of France. Originally part of the Louis Delhaize Group, it was recently acquired by the Carrefour Group to strengthen its market share in those regions. There are 115 Supermarch Match Supermarkets as of 27 May 2026 in France.

Supermarché Match is a supermarket chain operating primarily in the north and east of France. Originally part of the Louis Delhaize Group, it was recently acquired by the Carrefour Group to strengthen its market share in those regions.

There are 115 Supermarché Match Supermarkets as of 27 May 2026 in France. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Supermarché Match 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: 115 Supermarché Match supermarkets in France
  • 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: 27 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
  • 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

Data Quality Scorecard

  • Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
  • Contact Details (Phone)99%
  • Web Address99%
  • Opening Hours99%
  • Popularity Score100%

Data Preview: Sample geospatial records from the Supermarché Match dataset in France

ID Location Title Latitude Longitude Postal Code Full Address
d8a6051... Supermarché Match (Cysoing) 50.566859 3.223599 59830 Rue Félix Demesmay, Cysoing, 59830, N...
379373d... Supermarché Match (Maubeuge) 50.275130 3.967541 59600 Boulevard de l'Europe, Maubeuge, 5960...
e7770c5... Supermarché Match (Marcq-en-Barœul) 50.666890 3.077345 59700 Rue nationale, Marcq-en-Barœul, 59700...
dd54d2d... Supermarché Match (Lambersart) 50.637076 3.024926 59130 250 Avenue de Dunkerque, Lambersart, ...
4c2b7e0... Supermarché Match (Hettange-Grande) 49.417280 6.136665 57330 9 Rue des Ateliers, Hettange-Grande, ...

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 27 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 Supermarché Match locations in France is found in Grand Est (62 sites, equivalent to 1.09 Supermarché Match supermarkets per 100,000 residents). This is followed by Hauts-De-France (51 sites; 0.84 per 100,000) and Bourgogne-Franche-Comté (1 sites; 0.04 per 100,000). From a market-penetration perspective, Grand Est has the highest brand density at 1.09 locations per 100,000 people (population: 5,675,000), making it the most saturated region for Supermarché Match in France. By contrast, Île-De-France records only 0.01 locations per 100,000 residents (population: 12,610,000), 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 France

Brand bundle

Top 19 Grocery Brands in France - €400

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 Grocery Locations in France - 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 →

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].

Who uses this data?

  • Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
  • Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
  • Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
  • Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
  • Store Closure & Relocation Strategy: Corporate teams optimizing existing footprints by analyzing underperforming regions.
  • Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
  • CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
  • B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).

Frequently Asked Questions

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 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 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: Does the dataset include all locations in the country?

A: The dataset is designed to provide a complete and standardized list of known Supermarché Match locations operating in France as of 27 May 2026.

Q: Are phone numbers and websites included?

A: Yes. Where available, the dataset includes standardized phone numbers and official website URLs.

Q: Does the dataset include opening hours?

A: Yes, opening hours are included where publicly available and validated during the data standardization process.

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: 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.

Analyze this data with AI

Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:

  • "Analyze this Supermarché Match dataset to identify underserved regions in France for potential market expansion."
  • "Identify potential regional logistics bottlenecks caused by uneven geographic distribution of Supermarché Match locations in France."
  • "Using this Supermarché Match data, find high-traffic retail corridors in France with low supermarkets density for competitive positioning."

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.

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