Stokrotka Supermarket Locations Dataset – Poland

Stokrotka Supermarket Locations Dataset – PolandQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Stokrotka is a major Polish supermarket and proximity store chain owned by the Maxima Group. It has grown rapidly across the country, offering both large supermarkets and smaller "Stokrotka Express" urban formats. There are 986 Stokrotka Supermarkets as of 30 May 2026 in Poland. This dataset is compiled and

Stokrotka is a major Polish supermarket and proximity store chain owned by the Maxima Group. It has grown rapidly across the country, offering both large supermarkets and smaller "Stokrotka Express" urban formats.

There are 986 Stokrotka Supermarkets as of 30 May 2026 in Poland. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Stokrotka 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 Stokrotka dataset in Poland

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 Stokrotka locations in Poland is found in Lubelskie (273 sites, equivalent to 13.68 Stokrotka supermarkets per 100,000 residents). This is followed by Mazowieckie (121 sites; 2.2 per 100,000) and Śląskie (94 sites; 2.19 per 100,000). From a market-penetration perspective, Lubelskie has the highest brand density at 13.68 locations per 100,000 people (population: 1,995,000), making it the most saturated region for Stokrotka in Poland. By contrast, Wielkopolskie records only 0.89 locations per 100,000 residents (population: 3,495,000), 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 Stokrotka 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 Stokrotka 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?

• 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.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
• Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
• CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
• Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.

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 Stokrotka dataset to identify underserved regions in Poland for potential market expansion."
• "Identify high-income or high-density residential zones in Poland that currently lack nearby Stokrotka locations."
• "Measure average inter-store distance between Stokrotka locations across different regions of 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.