Lidl EV Charging Station Locations Dataset – Poland

Lidl is a prominent discount supermarket chain in Poland known for its high-quality products at competitive prices. Enhancing its customer shopping experience and environmental commitment, it has deployed electric vehicle charging infrastructure at many of its store parking lots.

There are 710 Lidl EV Charging Stations as of 2 June 2026 in Poland. 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 Poland

ID	Location Title	Latitude	Longitude	Postal Code	Full Address
694be68...	Lidl Charging Station	50.406699	21.753929	39-460	2e Bieszczadzka, Nowa Dęba, 39-460, P...
246adef...	Lidl Charging Station	54.383659	18.597262	80-266	161 aleja Grunwaldzka, Gdańsk, 80-266...
12834b9...	Lidl Charging Station	51.159949	15.007463	59-900	1A Księdza Jana Kozaka, Zgorzelec, 59...
29ad768...	Lidl Charging Station	54.375921	18.524368	80-298	21 Złota Karczma, Gdańsk, 80-298, Pow...
bbb2845...	Lidl Charging Station	52.722344	15.250915	66-400	35 Rondo Grobla, Gorzów Wielkopolski,...

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.

✅ 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 Poland is found in Śląskie (103 sites, equivalent to 2.4 Lidl ev charging stations per 100,000 residents). This is followed by Mazowieckie (75 sites; 1.36 per 100,000) and Wielkopolskie (74 sites; 2.12 per 100,000). From a market-penetration perspective, Zachodniopomorskie has the highest brand density at 2.78 locations per 100,000 people (population: 1,620,000), making it the most saturated region for Lidl in Poland. By contrast, Podkarpackie records only 1.17 locations per 100,000 residents (population: 2,060,000), indicating a potential white-space opportunity for network expansion or competitor analysis.

Also available for Poland

Related geospatial datasets

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

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?

• CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
• Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
• 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.
• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
• 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.

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 Poland for potential market expansion."
• "Map the concentration of Lidl locations relative to major retail centers and shopping districts in Poland."
• "Identify the most central Lidl locations in Poland 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.