Lidl Supermarket Locations Dataset – Belgium

Lidl Supermarket Locations Dataset – BelgiumQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Lidl is a major German international discount chain that has a strong presence in Belgium, emphasizing fresh produce and high quality price ratios. It has successfully shifted its image toward a 'smart discount' model in the country. There are 308 Lidl Supermarkets as of 26 May 2026 in Belgium. This dataset

Lidl is a major German international discount chain that has a strong presence in Belgium, emphasizing fresh produce and high quality-price ratios. It has successfully shifted its image toward a 'smart discount' model in the country.

There are 308 Lidl Supermarkets as of 26 May 2026 in Belgium. 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 Belgium

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of Lidl locations in Belgium is found in Province De Hainaut (54 sites, equivalent to 3.96 Lidl supermarkets per 100,000 residents). This is followed by Province D'Anvers (49 sites; 2.55 per 100,000) and Province De Flandre Orientale (37 sites; 2.31 per 100,000). From a market-penetration perspective, Province De Hainaut has the highest brand density at 3.96 locations per 100,000 people (population: 1,365,000), making it the most saturated region for Lidl in Belgium. By contrast, Région De Bruxelles-Capitale records only 1.35 locations per 100,000 residents (population: 1,255,000), 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 Belgium

Related geospatial datasets

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

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?

• Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
• Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
• Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
• Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
• Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
• 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

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 Belgium for potential market expansion."
• "Identify locations where multiple Lidl sites compete within overlapping catchment areas in Belgium."
• "Identify the most central Lidl locations in Belgium to serve as hubs for a last-mile delivery network."

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.