Intermarche Supermarket Locations Dataset – Poland

Intermarche Supermarket Locations Dataset – PolandQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Intermarch is a major supermarket and hypermarket chain in Poland operated by independent entrepreneurs under the Les Mousquetaires group. It is unique for its integrated supply chain and its focus on fresh products and in store smoking rooms for meats. There are 196 Intermarche Supermarkets as of 30 May 2026

Intermarché is a major supermarket and hypermarket chain in Poland operated by independent entrepreneurs under the Les Mousquetaires group. It is unique for its integrated supply chain and its focus on fresh products and in-store smoking rooms for meats.

There are 196 Intermarche Supermarkets as of 30 May 2026 in Poland. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Intermarche 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 Intermarche dataset in Poland

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of Intermarche locations in Poland is found in Wielkopolskie (35 sites, equivalent to 1.0 Intermarche supermarkets per 100,000 residents). This is followed by Dolnośląskie (28 sites; 0.98 per 100,000) and Zachodniopomorskie (24 sites; 1.48 per 100,000). From a market-penetration perspective, Lubuskie has the highest brand density at 2.18 locations per 100,000 people (population: 965,000), making it the most saturated region for Intermarche in Poland. By contrast, Podlaskie records only 0.09 locations per 100,000 residents (population: 1,140,000), 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 Intermarche 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 Intermarche 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?

• 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.
• 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.
• Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
• Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
• Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.

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 Intermarche dataset to identify underserved regions in Poland for potential market expansion."
• "Identify the most central Intermarche locations in Poland to serve as hubs for a last-mile delivery network."
• "Identify high-income or high-density residential zones in Poland that currently lack nearby Intermarche locations."

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.