Lidl Supermarket Locations Dataset – Netherlands

Lidl Supermarket Locations Dataset – NetherlandsQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Lidl has a massive presence in the Netherlands, consistently winning awards for the quality of its fresh fruits and vegetables. It is a dominant force in the Dutch discount segment, focusing on efficiency and a high quality private label assortment. There are 449 Lidl Supermarkets as of 26 May 2026 in the

Lidl has a massive presence in the Netherlands, consistently winning awards for the quality of its fresh fruits and vegetables. It is a dominant force in the Dutch discount segment, focusing on efficiency and a high-quality private-label assortment.

There are 449 Lidl Supermarkets as of 26 May 2026 in the Netherlands. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Lidl 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 Lidl dataset in Netherlands

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 Lidl locations in the Netherlands is found in Zuid-Holland (90 sites, equivalent to 2.33 Lidl supermarkets per 100,000 residents). This is followed by Noord-Brabant (73 sites; 2.74 per 100,000) and Gelderland (55 sites; 2.55 per 100,000). From a market-penetration perspective, Zeeland has the highest brand density at 3.85 locations per 100,000 people (population: 390,000), making it the most saturated region for Lidl in the Netherlands. By contrast, Utrecht records only 1.78 locations per 100,000 residents (population: 1,405,000), 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 the Netherlands

Related geospatial datasets

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

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?

• Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
• Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
• Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
• Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
• Vendor Distribution: FMCG and wholesale suppliers identifying specific retail locations for direct-store-delivery (DSD) pitching.
• Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.

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 Lidl dataset to identify underserved regions in the Netherlands for potential market expansion."
• "Analyze which Lidl locations in the Netherlands are positioned in highly competitive retail zones versus standalone markets."
• "Assess the accessibility of Lidl locations in the Netherlands based on proximity to population centers and public infrastructure."

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.