Kaufland EV Charging Station Locations Dataset – Poland

Kaufland is a major hypermarket chain operating widely across Poland, offering a vast assortment of groceries and household goods. To support sustainable practices, many of its retail locations are equipped with electric vehicle charging stations for customer convenience.

There are 204 Kaufland 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 Kaufland 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 Kaufland dataset in Poland

ID	Location Title	Latitude	Longitude	Postal Code	Full Address
745af72...	Kaufland Charging Station	54.183397	17.494493	77-100	15 Generała Józefa Wybickiego, Bytów,...
bf7460f...	Kaufland Charging Station	52.629710	20.381787	09-100	16 Żołnierzy Wyklętych, Płońsk, 09-10...
c3daf7e...	Kaufland Charging Station	52.740916	23.587162	17-200	18 Stefana Batorego, Hajnówka, 17-200...
a4d2515...	Kaufland Charging Station	51.213192	22.712218	21-040	3 Krępiecka, Świdnik, 21-040, Powiat ...
fc9948f...	Kaufland Charging Station	52.538437	17.611766	62-200	46 Franklina Roosevelta, Gniezno, 62-...

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 Kaufland locations in Poland is found in Śląskie (34 sites, equivalent to 0.79 Kaufland ev charging stations per 100,000 residents). This is followed by Mazowieckie (25 sites; 0.45 per 100,000) and Wielkopolskie (23 sites; 0.66 per 100,000). From a market-penetration perspective, Śląskie has the highest brand density at 0.79 locations per 100,000 people (population: 4,290,000), making it the most saturated region for Kaufland in Poland. By contrast, Małopolskie records only 0.2 locations per 100,000 residents (population: 3,430,000), 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 Kaufland 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 Kaufland 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?

• Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
• 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.
• 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.
• 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 Kaufland dataset to identify underserved regions in Poland for potential market expansion."
• "Generate regional density heatmaps showing where Kaufland has the strongest and weakest retail presence in Poland."
• "Evaluate how evenly Kaufland locations are distributed across provinces, districts, or municipalities in Poland."

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.