Kaufland EV Charging Station Locations Dataset – Poland
SKU: 32186680241

Kaufland EV Charging Station Locations Dataset – Poland

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Description

Kaufland EV Charging Station Locations Dataset – PolandQuick links: Dataset Summary Methodology Download Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI 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

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 Summary

  • Dataset Coverage: 204 Kaufland ev charging stations in Poland
  • Contents: Coordinates, addresses, postal codes, and administrative divisions
  • 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: 2 June 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
  • Municipality
  • Region
  • Population
  • Postal Code
  • Address

Require additional attributes such as charging points, charger types, or charging speed? Contact us to request a custom data enrichment.

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.

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 2 June 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 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

Brand bundle

Top 21 EV Charging Stations Brands in Poland - €240

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 EV Charging Stations Locations in Poland - 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 →

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?

  • 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

Q: Is this dataset useful for accessibility studies?

A: Yes. Analysts can combine the coordinates with mobility, transport, and demographics datasets to evaluate accessibility and service coverage.

Q: Are postal codes included for all locations?

A: Postal codes are included wherever available and validated as part of the standardization workflow.

Q: How accurate are the coordinates?

A: Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.

Q: Are the datasets suitable for machine learning workflows?

A: Yes. The structured tabular format and standardized coordinates make the datasets suitable for machine learning and predictive analytics applications.

Q: Can I request custom enrichment fields?

A: Yes. Custom enrichment services may be available depending on the project scope and geographic coverage requirements.

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.

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SKU: 32186680241

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