Biedronka Supermarket Locations Dataset – Poland

Biedronka Supermarket Locations Dataset – PolandQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Biedronka is the largest and most recognizable supermarket chain in Poland, owned by the Portuguese group Jernimo Martins. It is the dominant market leader, famous for its ladybug logo and its massive network of over 3,600 stores nationwide. There are 3,900 Biedronka Supermarkets as of 30 May 2026 in Poland.

Biedronka is the largest and most recognizable supermarket chain in Poland, owned by the Portuguese group Jerónimo Martins. It is the dominant market leader, famous for its ladybug logo and its massive network of over 3,600 stores nationwide.

There are 3,900 Biedronka Supermarkets as of 30 May 2026 in Poland. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Biedronka 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 Quality Scorecard

Data Preview: Sample geospatial records from the Biedronka dataset in Poland

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of Biedronka locations in Poland is found in Mazowieckie (521 sites, equivalent to 9.46 Biedronka supermarkets per 100,000 residents). This is followed by Śląskie (448 sites; 10.44 per 100,000) and Wielkopolskie (369 sites; 10.56 per 100,000). From a market-penetration perspective, Lubuskie has the highest brand density at 13.58 locations per 100,000 people (population: 965,000), making it the most saturated region for Biedronka in Poland. By contrast, Małopolskie records only 8.34 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 Biedronka 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 Biedronka 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 [email protected].

Who uses this data?

• Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
• Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
• Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
• 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.
• 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 Biedronka dataset to identify underserved regions in Poland for potential market expansion."
• "Identify fast-growing suburban areas in Poland that currently have limited access to nearby supermarkets."
• "Identify Biedronka sites with large footprints in Poland that are optimal candidates for EV charging infrastructure overlays."

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.