Lidl Supermarket Locations Dataset – Portugal

Lidl Supermarket Locations Dataset – PortugalQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Related Datasets Use Cases FAQ Analyze with AI Lidl Portugal is a dominant discount supermarket chain known for its efficiency and popular themed weeks featuring international products. It maintains a strong commitment to Portuguese producers, with a significant portion of its fresh goods sourced locally. There are 286 Lidl Supermarkets as of 28 May 2026 in Portugal.

Lidl Portugal is a dominant discount supermarket chain known for its efficiency and popular themed weeks featuring international products. It maintains a strong commitment to Portuguese producers, with a significant portion of its fresh goods sourced locally.

There are 286 Lidl Supermarkets as of 28 May 2026 in Portugal. 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 Portugal

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 Portugal is found in Pop - Évora (160073 sites). This is followed by Pop - Bragança (128949 sites) and Lisboa (64 sites; 2.68 per 100,000). From a market-penetration perspective, Beja has the highest brand density at 4.0 locations per 100,000 people (population: 150,000), making it the most saturated region for Lidl in Portugal. By contrast, Vila Real records only 1.05 locations per 100,000 residents (population: 190,000), indicating a potential white-space opportunity for network expansion or competitor analysis.

Related geospatial datasets

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

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?

• CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
• Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
• Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
• 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.

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 Portugal for potential market expansion."
• "Identify the most central Lidl locations in Portugal to serve as hubs for a last-mile delivery network."
• "Analyze which Lidl locations in Portugal are positioned in highly competitive retail zones versus standalone markets."

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.