SKU: 48651632735

Mix Markt Supermarket Locations Dataset – Germany

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Description

Mix Markt Supermarket Locations Dataset – GermanyQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Mix Markt is a specialized supermarket chain in Germany focusing on Eastern European and international products. It is the leading retailer for consumers looking for Slavic, Baltic, and Balkan food specialties. There are 199 Mix Markt Supermarkets as of 27 May 2026 in Germany. This dataset is compiled and

Mix Markt is a specialized supermarket chain in Germany focusing on Eastern European and international products. It is the leading retailer for consumers looking for Slavic, Baltic, and Balkan food specialties.

There are 199 Mix Markt Supermarkets as of 27 May 2026 in Germany. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Mix Markt 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: 199 Mix Markt supermarkets in Germany
  • 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: 27 May 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
  • Area
  • City
  • Admin_level_1
  • Admin_level_2
  • Gemainde
  • Federal State
  • Population
  • Postal Code
  • Address
  • Wheelchair
  • Popularity Score
  • Phone
  • Website
  • Opening hours

Data Quality Scorecard

  • Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
  • Contact Details (Phone)96%
  • Web Address96%
  • Opening Hours98%
  • Popularity Score100%

Data Preview: Sample geospatial records from the Mix Markt dataset in Germany

ID Location Title Latitude Longitude Postal Code Full Address
56a37df... Mix Markt (Waldkraiburg) 48.198882 12.393664 84478 25g Aussiger Straße, Waldkraiburg, 84...
6556d1d... Mix Markt (Sindelfingen) 48.705811 8.998334 71063 12 Mercedesstraße, Sindelfingen, 7106...
d2d166c... Mix Markt (Bad Hersfeld) 50.864653 9.712444 36251 3 Hainchenweg, Bad Hersfeld, 36251, K...
b146acf... Mix Markt (Augustdorf) 51.908061 8.726173 32832 15 Stukenbrocker Straße, Augustdorf, ...
0d6b391... Mix Markt (Hamm-Heessen) 51.692167 7.803218 59065 23 Großer Sandweg, Hamm, 59065, Arnsb...

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 27 May 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 Mix Markt locations in Germany is found in Nordrhein-Westfalen (48 sites, equivalent to 0.27 Mix Markt supermarkets per 100,000 residents). This is followed by Bayern (42 sites; 0.32 per 100,000) and Baden-Württemberg (40 sites; 0.36 per 100,000). From a market-penetration perspective, Baden-Württemberg has the highest brand density at 0.36 locations per 100,000 people (population: 11,170,000), making it the most saturated region for Mix Markt in Germany. By contrast, Berlin records only 0.05 locations per 100,000 residents (population: 3,690,000), 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 Germany

Brand bundle

Top 27 Grocery Brands in Germany - €480

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 Germany - 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 →

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?

  • 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.
  • Store Closure & Relocation Strategy: Corporate teams optimizing existing footprints by analyzing underperforming regions.
  • 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.
  • B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
  • Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.

Frequently Asked Questions

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: Does the dataset include unique identifiers?

A: Yes. Each record includes a GUID field to support deduplication, joins, and downstream database operations.

Q: Are postal codes included for all locations?

A: Postal codes are included wherever available and validated as part of the standardization workflow.

Q: Can I request custom enrichment fields?

A: Yes. Custom enrichment services may be available depending on the project scope and geographic coverage requirements.

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: What coordinate reference system is used?

A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).

Q: How accurate are the coordinates?

A: Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.

Q: Can this data be combined with demographics datasets?

A: Yes. Many customers combine these locations with demographics, income, mobility, and administrative boundary datasets for deeper spatial analysis.

Analyze this data with AI

Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:

  • "Analyze this Mix Markt dataset to identify underserved regions in Germany for potential market expansion."
  • "Identify high-income or high-density residential zones in Germany that currently lack nearby Mix Markt locations."
  • "Identify isolated Mix Markt sites in Germany that may face operational inefficiencies due to low regional clustering."

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.

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Reviewed in the United States on October 7, 2025
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New York, US
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