Nasz Sklep Supermarket Locations Dataset – Poland
Nasz Sklep Supermarket Locations Dataset – Poland
Nasz Sklep is a large Polish retail network belonging to the Specjał Group, operating primarily through a franchise model. It focuses on providing a wide range of groceries in small to medium-sized proximity stores across the country.
There are 292 Nasz Sklep Supermarkets as of 4 August 2026 in Poland. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Nasz Sklep 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: 292 Nasz Sklep supermarkets in Poland
- Contents: Coordinates, addresses, postal codes, administrative divisions, contact details, and popularity scores
- 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: 4 August 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
- Wheelchair
- Popularity Score
- Phone
- Website
- Opening hours
Data Quality Scorecard
- Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
- Contact Details (Phone)27%
- Web Address27%
- Opening Hours74%
- Popularity Score100%
Data Preview: Sample geospatial records from the Nasz Sklep dataset in Poland
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 281ceef... | Nasz Sklep (Oleszyce) | 50.167798 | 23.031544 | 37-630 | 16 Rynek, Oleszyce, 37-630, Powiat lu... |
| 4719a3e... | Nasz Sklep (Chorupnik) | 50.936910 | 22.998412 | 22-315 | Chorupnik, 22-315, Powiat krasnostaws... |
| 64382fd... | Nasz Sklep (Chotylub) | 50.235662 | 23.214713 | 37-611 | Chotylub, 37-611, Powiat lubaczowski,... |
| 5c1db1d... | Nasz Sklep (Jarosław) | 50.037670 | 22.675594 | 37-500 | 66 Dolnoleżajska, Jarosław, 37-500, P... |
| fa5fa23... | Nasz Sklep (Widzew) | 51.761917 | 19.492832 | 92-332 | 117 aleja marsz. Józefa Piłsudskiego,... |
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 4 August 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 Nasz Sklep locations in Poland is found in Podkarpackie (109 sites, equivalent to 5.29 Nasz Sklep supermarkets per 100,000 residents). This is followed by Lubelskie (73 sites; 3.66 per 100,000) and Łódzkie (28 sites; 1.19 per 100,000). From a market-penetration perspective, Podkarpackie has the highest brand density at 5.29 locations per 100,000 people (population: 2,060,000), making it the most saturated region for Nasz Sklep in Poland. By contrast, Mazowieckie records only 0.07 locations per 100,000 residents (population: 5,505,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Also available for Poland
Brand bundle
Top 21 Grocery Brands in Poland - €400
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 Grocery 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 →Related geospatial datasets
- Administrative boundaries and full polygon dataset for Poland: Map these Nasz Sklep 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 Nasz Sklep 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?
- Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
- 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.
- Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
- Vendor Distribution: FMCG and wholesale suppliers identifying specific retail locations for direct-store-delivery (DSD) pitching.
- CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
- Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
- Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
- 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: Can this dataset be used for academic or research purposes?
A: Yes. Researchers and universities frequently use these datasets for urban studies, geography, economics, and spatial analytics projects.
Q: Can I integrate this dataset into a PostgreSQL/PostGIS database?
A: Yes. The dataset structure is compatible with PostgreSQL/PostGIS and other relational spatial databases.
Q: Does the dataset include administrative regions?
A: Yes. Administrative fields such as province, district, municipality, postal code, and city are included where available.
Q: Can I analyze this dataset with AI tools?
A: Yes. The dataset is structured for compatibility with AI workflows including ChatGPT, Claude, Gemini, RAG pipelines, and Python-based analytics.
Q: How accurate are the coordinates?
A: Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.
Q: Does the dataset include accessibility-related attributes?
A: Yes. Certain datasets include accessibility-related indicators such as wheelchair accessibility where publicly available.
Q: Is the dataset standardized for analytics workflows?
A: Yes. Address formatting, administrative areas, and geospatial fields are standardized to improve consistency across analytical environments.
Q: Are phone numbers and websites included?
A: Yes. Where available, the dataset includes standardized phone numbers and official website URLs.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this Nasz Sklep dataset to identify underserved regions in Poland for potential market expansion.""Identify isolated Nasz Sklep sites in Poland that may face operational inefficiencies due to low regional clustering.""Using this Nasz Sklep data, find high-traffic retail corridors in Poland with low supermarkets density for competitive positioning."
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.