Lidl EV Charging Station Locations Dataset – Greece

Lidl Hellas, the Greek arm of German discount supermarket chain Lidl (part of the Schwarz Gruppe), installs its own EV chargers at its supermarket car parks nationwide. Charging was originally free for all drivers but became a paid service after reports of misuse.

There are 94 Lidl EV Charging Stations as of 13 July 2026 in Greece. 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 Preview: Sample geospatial records from the Lidl dataset in Greece

ID	Location Title	Latitude	Longitude	Postal Code	Full Address
7897775...	Lidl Charging Station	40.561276	23.021940	552 36	4 Agion Anargiron, Panorama, 552 36, ...
5d137e1...	Lidl Charging Station	40.466618	22.866692	570 04	19 Imvroi, Nea Michaniona, 570 04, Gr...
0368ccc...	Lidl Charging Station	40.560882	23.021952	552 36	Panorama, 552 36, Greece
a4ac448...	Lidl Charging Station	40.540531	22.210731	591 00	Αλεξανδρείας, Βέροια, 591 00, Greece
18be168...	Lidl Charging Station	35.314380	25.141514	714 09	144 Leoforos Papanastasiou, Iraklio, ...

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 Greece is found in Περιφέρεια Αττικής (30 sites, equivalent to 0.77 Lidl ev charging stations per 100,000 residents). This is followed by Περιφέρεια Κεντρικής Μακεδονίας (25 sites; 1.39 per 100,000) and Περιφέρεια Δυτικής Ελλάδας (10 sites; 1.57 per 100,000). From a market-penetration perspective, Περιφέρεια Δυτικής Ελλάδας has the highest brand density at 1.57 locations per 100,000 people (population: 635,000), making it the most saturated region for Lidl in Greece. By contrast, Περιφέρεια Στερεάς Ελλάδας records only 0.2 locations per 100,000 residents (population: 500,000), indicating a potential white-space opportunity for network expansion or competitor analysis.

Also available for Greece

Related geospatial datasets

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

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 contact@geolocet.com.

Who uses this data?

• Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
• Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
• Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
• 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.
• B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
• 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.

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 Greece for potential market expansion."
• "Map the concentration of Lidl locations relative to major retail centers and shopping districts in Greece."
• "Using this Lidl data, find high-traffic retail corridors in Greece with low ev charging stations density for competitive positioning."

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.