Netto Supermarket Locations Dataset – France

Netto Supermarket Locations Dataset – FranceQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Netto is a French discount supermarket chain owned by the Les Mousquetaires group, operating completely independently from the Danish chain of the same name. It focuses on providing essential groceries and private label products at hard discount prices. There are 449 Netto Supermarkets as of 27 May 2026 in

Netto is a French discount supermarket chain owned by the Les Mousquetaires group, operating completely independently from the Danish chain of the same name. It focuses on providing essential groceries and private-label products at hard-discount prices.

There are 449 Netto Supermarkets as of 27 May 2026 in France. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Netto locations, including full address details, administrative divisions, and precise WGS84 latitude/longitude coordinates - structured for GIS, retail analytics, mapping, and AI/RAG workflows.

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.

Data Quality Scorecard

Data Preview: Sample geospatial records from the Netto dataset in France

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.

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of Netto locations in France is found in Auvergne-Rhône-Alpes (95 sites, equivalent to 1.14 Netto supermarkets per 100,000 residents). This is followed by Occitanie (64 sites; 1.03 per 100,000) and Nouvelle-Aquitaine (60 sites; 0.96 per 100,000). From a market-penetration perspective, Bourgogne-Franche-Comté has the highest brand density at 1.97 locations per 100,000 people (population: 2,840,000), making it the most saturated region for Netto in France. By contrast, Île-De-France records only 0.1 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

Related geospatial datasets

• Administrative boundaries and full polygon dataset for France: Map these Netto locations against highly precise administrative polygons for territory analysis and spatial structuring.
• Demographics dataset for France: Overlay demographic indicators to deeply understand the population structures and household types surrounding these Netto locations.
• Explore demographics data insights for France: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
• Income indicators dataset for France (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 France - 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 France-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 France

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?

• Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
• Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
• B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
• Vendor Distribution: FMCG and wholesale suppliers identifying specific retail locations for direct-store-delivery (DSD) pitching.
• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
• Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
• Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.

Frequently Asked Questions

Analyze this data with AI

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

• "Analyze this Netto dataset to identify underserved regions in France for potential market expansion."
• "Generate regional density heatmaps showing where Netto has the strongest and weakest retail presence in France."
• "Detect clusters where Netto sites are in close proximity to analyze potential self-cannibalization in France."

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.