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Description
Lidl Supermarket Locations Dataset – ItalyQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Lidl has a long standing and highly successful presence in Italy, operating hundreds of stores from the Alps to Sicily. It is recognized for its ability to integrate international logistics with a high percentage of "Made in Italy" products. There are 851 Lidl Supermarkets as of 28 May 2026 in Italy. This
Lidl has a long-standing and highly successful presence in Italy, operating hundreds of stores from the Alps to Sicily. It is recognized for its ability to integrate international logistics with a high percentage of "Made in Italy" products.
There are 851 Lidl Supermarkets as of 28 May 2026 in Italy. 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 Summary
- Dataset Coverage: 851 Lidl supermarkets in Italy
- Contents: Coordinates, addresses, postal codes, administrative divisions, contact details, and popularity scores
- File Format: Fully geocoded CSV dataset (UTF-8)
- Free Sample: Instantly accessible dataset to verify structure and data quality
- Use Cases: Suitable for GIS, retail analytics, site selection, and AI/RAG workflows
- Last Updated: 28 May 2026
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.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- City
- Admin_level_1
- Admin_level_2
- Commune
- Region
- Population
- Postal Code
- Address
- Wheelchair
- Popularity Score
- Phone
- Website
- Opening hours
Data Quality Scorecard
- Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
- Contact Details (Phone)87%
- Web Address88%
- Opening Hours88%
- Popularity Score100%
Data Preview: Sample geospatial records from the Lidl dataset in Italy
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| f8a32e5... | Lidl (Milano) | 45.447439 | 9.209425 | 20135 | 38 Piazzale Lodi, Milano, 20135, Citt... |
| 51f3073... | Lidl (Verbania) | 45.928439 | 8.552067 | 28922 | Corso Nazioni Unite, Verbania, 28922,... |
| 0823a6b... | Lidl | 37.281291 | 14.988065 | 96016 | snc Via Francofonte, 96016, Libero co... |
| 43f384b... | Lidl (Omegna) | 45.884951 | 8.408750 | 28887 | 35 Via IV Novembre, Omegna, 28887, Pr... |
| 129d29d... | Lidl | 41.207972 | 16.554278 | 70056 | 16 Via A. Olivetti, 70056, Città Metr... |
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.
Why download from Geolocet?
- Instant download - full dataset available immediately after purchase, no waiting, no manual fulfilment
- Free sample first - verify structure, fields, and coordinate precision before you commit
- Analysis-ready CSV - clean, standardised, and compatible with Excel, Python, QGIS, Power BI, and PostgreSQL out of the box
- Regularly updated - last updated 28 May 2026
✅ Data looks right? Add to cart ↑ - or download the free sample first.
Regional Distribution Breakdown
Looking at the geographic distribution, the highest concentration of Lidl locations in Italy is found in Pop - Sardigna (1562381 sites). This is followed by Pop - Liguria (1510143 sites) and Pop - Abruzzo (1269118 sites). From a market-penetration perspective, Friuli-Venezia Giulia has the highest brand density at 3.03 locations per 100,000 people (population: 1,190,000), making it the most saturated region for Lidl in Italy. By contrast, Basilicata records only 0.38 locations per 100,000 residents (population: 530,000), 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 Italy
Brand bundle
Top 13 Grocery Brands in Italy - €300
All major chains in one standardised dataset. Best for competitive benchmarking, network analysis, and market sizing across the leading brands.
View Top Brands dataset →Full market coverage
All Grocery Locations in Italy - complete POI dataset
Includes everything in the brand bundle plus independent operators, smaller chains, and local businesses not covered by the top brands. Best for full market mapping, territory planning, and white-space analysis.
View full POI dataset →Related geospatial datasets
- Administrative boundaries and full polygon dataset for Italy: Map these Lidl locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Italy: Overlay demographic indicators to deeply understand the population structures and household types surrounding these Lidl locations.
- Explore demographics data insights for Italy: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for Italy (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 Italy-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 Italy
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.
- Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
- 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.
- Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
- Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
- Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
- Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
- Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
Frequently Asked Questions
Q: Can I analyze this dataset with AI tools?
A: Yes. The dataset is structured for compatibility with AI workflows including ChatGPT, Claude, Gemini, RAG pipelines, and Python-based analytics.
Q: Can this dataset support expansion planning?
A: Yes. Analysts often use the dataset to identify underserved areas, evaluate regional density, and support retail expansion decisions.
Q: Can this data be combined with demographics datasets?
A: Yes. Many customers combine these locations with demographics, income, mobility, and administrative boundary datasets for deeper spatial analysis.
Q: Can I preview the dataset before purchasing?
A: Yes. A free sample is available so you can evaluate the structure, fields, and geospatial quality before purchase.
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 Italy for potential market expansion.""Compare the spatial distribution of Lidl locations against major competitor clusters to identify overlap and whitespace opportunities in Italy.""Identify the most central Lidl locations in Italy 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.
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