Lidl Supermarket Locations Dataset – Switzerland

Lidl Supermarket Locations Dataset – SwitzerlandQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Related Datasets Use Cases FAQ Analyze with AI Lidl Schweiz offers a modern discount shopping experience with a strong emphasis on efficiency and fresh daily supplies. It has grown rapidly in Switzerland by positioning its stores in prime urban and suburban locations. There are 193 Lidl Supermarkets as of 30 May 2026 in Switzerland. This dataset is compiled and

Lidl Schweiz offers a modern discount shopping experience with a strong emphasis on efficiency and fresh daily supplies. It has grown rapidly in Switzerland by positioning its stores in prime urban and suburban locations.

There are 193 Lidl Supermarkets as of 30 May 2026 in Switzerland. 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 Switzerland

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of Lidl locations in Switzerland is found in Appenzell Innerrhoden (16733 sites). This is followed by Zürich (30 sites; 1.85 per 100,000) and Aargau (17 sites; 2.31 per 100,000). From a market-penetration perspective, Amtei Olten-Gösgen has the highest brand density at 5.0 locations per 100,000 people (population: 80,000), making it the most saturated region for Lidl in Switzerland. By contrast, Basel-Stadt records only 0.5 locations per 100,000 residents (population: 200,000), indicating a potential white-space opportunity for network expansion or competitor analysis.

Related geospatial datasets

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

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?

• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
• Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
• 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.
• Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
• Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
• Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
• Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.

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 Switzerland for potential market expansion."
• "Rank the top-performing urban areas in Switzerland for future Lidl expansion based on existing location density and regional population."
• "Map the concentration of Lidl locations relative to major retail centers and shopping districts in Switzerland."

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.