MD Supermarket Locations Dataset – Italy

MD Supermarket Locations Dataset – ItalyQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI MD is a leading Italian discount retailer that has grown rapidly through acquisitions and organic expansion. It focuses on the "Good and Italian" philosophy, offering a wide range of affordable private labels in a modern store environment. There are 931 MD Supermarkets as of 28 May 2026 in Italy. This dataset

MD is a leading Italian discount retailer that has grown rapidly through acquisitions and organic expansion. It focuses on the "Good and Italian" philosophy, offering a wide range of affordable private labels in a modern store environment.

There are 931 MD Supermarkets as of 28 May 2026 in Italy. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all MD 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 MD dataset in Italy

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 MD locations in Italy is found in Pop - Sardigna (1562381 sites). This is followed by Pop - Liguria (1510143 sites) and Pop - Abruzzo (1269118 sites). From a market-penetration perspective, Molise has the highest brand density at 4.21 locations per 100,000 people (population: 285,000), making it the most saturated region for MD in Italy. By contrast, Friuli-Venezia Giulia records only 0.25 locations per 100,000 residents (population: 1,190,000), indicating a potential white-space opportunity for network expansion or competitor analysis.

Learn more about the brand network in our report: View Report

Also available for Italy

Related geospatial datasets

• Administrative boundaries and full polygon dataset for Italy: Map these MD locations against highly precise administrative polygons for territory analysis and spatial structuring.
• Demographics dataset for Italy: Overlay demographic indicators to deeply understand the population structures and household types surrounding these MD locations.
• Explore demographics data insights for Italy: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
• Income indicators dataset for Italy (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 Italy-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 Italy

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?

• Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
• 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.
• Store Closure & Relocation Strategy: Corporate teams optimizing existing footprints by analyzing underperforming regions.
• Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
• CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
• 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 MD dataset to identify underserved regions in Italy for potential market expansion."
• "Identify potential regional logistics bottlenecks caused by uneven geographic distribution of MD locations in Italy."
• "Cross-reference these supermarkets with urban transit data to score each location's accessibility for non-driving customers."

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.