Dino Supermarket Locations Dataset – Poland

Dino is a high-growth Polish proximity supermarket chain that has become one of the fastest-growing retailers in Europe. It focuses on mid-sized stores located in smaller towns and rural areas, offering a consistent layout and strong meat departments.

There are 3,113 Dino Supermarkets as of 30 May 2026 in Poland. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Dino 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 Dino dataset in Poland

ID	Location Title	Latitude	Longitude	Postal Code	Full Address
e9f4967...	Dino (Chrzan)	52.071771	17.510487	63-210	2A Długa, Chrzan, 63-210, Powiat jaro...
9fcf123...	Dino (Kłoda)	51.771183	16.643746	64-130	Kłoda, 64-130, Powiat leszczyński, Po...
fbf3551...	Dino (Racibórz)	50.091771	18.211596	47-400	6 Karola Miarki, Racibórz, 47-400, Po...
7d4ba65...	Dino (Jacków)	50.965010	19.328993	42-282	116 Główna, Jacków, 42-282, Powiat cz...
6ae1128...	Market Dino (Wińsko)	51.466895	16.609257	56-160	12 Wincentego Witosa, Wińsko, 56-160,...

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 Dino locations in Poland is found in Wielkopolskie (629 sites, equivalent to 18.0 Dino supermarkets per 100,000 residents). This is followed by Dolnośląskie (329 sites; 11.48 per 100,000) and Mazowieckie (262 sites; 4.76 per 100,000). From a market-penetration perspective, Lubuskie has the highest brand density at 19.79 locations per 100,000 people (population: 965,000), making it the most saturated region for Dino in Poland. By contrast, Podkarpackie records only 2.04 locations per 100,000 residents (population: 2,060,000), 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 Dino 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 Dino 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?

• Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
• Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
• Store Closure & Relocation Strategy: Corporate teams optimizing existing footprints by analyzing underperforming regions.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
• B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.

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 Dino dataset to identify underserved regions in Poland for potential market expansion."
• "Identify potential regional logistics bottlenecks caused by uneven geographic distribution of Dino locations in Poland."
• "Assess how effectively the current Dino network covers major commercial and residential hubs across 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.