Konsum Supermarket Locations Dataset – Germany

Konsum Supermarket Locations Dataset – Germany

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Konsum refers to various regional consumer cooperatives in Germany, with notable presence in cities like Dresden and Leipzig. They focus on regional products and a community-oriented retail approach.

There are 124 Konsum Supermarkets as of 27 May 2026 in Germany. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Konsum 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: 124 Konsum 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.

Map showing the geographical distribution of Konsum locations in Germany

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)87%
  • Web Address70%
  • Opening Hours90%
  • Popularity Score100%

Data Preview: Sample geospatial records from the Konsum dataset in Germany

ID Location Title Latitude Longitude Postal Code Full Address
3454f5a... Konsum (Nordwest) 51.368182 12.345284 04159 17 Dantestraße, Leipzig, 04159, Germany
ef59ea1... Konsum (Alt-West) 51.338329 12.334983 04177 9 Demmeringstraße, Leipzig, 04177, Ge...
09b51b4... Konsum (Göppingen) 48.708436 9.636279 73033 67 Stuttgarter Straße, Göppingen, 730...
6630b9f... Konsum (Mitte) 51.349477 12.352747 04105 2 Goyastraße, Leipzig, 04105, Germany
adbfec1... Konsum (Banzkow) 53.524353 11.516912 19079 7 Schulsteig, Banzkow, 19079, Germany

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 Konsum locations in Germany is found in Sachsen (79 sites, equivalent to 1.95 Konsum supermarkets per 100,000 residents). This is followed by Mecklenburg-Vorpommern (16 sites; 0.99 per 100,000) and Sachsen-Anhalt (14 sites; 0.64 per 100,000). From a market-penetration perspective, Sachsen has the highest brand density at 1.95 locations per 100,000 people (population: 4,055,000), making it the most saturated region for Konsum in Germany. By contrast, Nordrhein-Westfalen records only 0.01 locations per 100,000 residents (population: 17,995,000), 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 contact@geolocet.com.

Who uses this data?

  • Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
  • 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).
  • Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
  • Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
  • Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
  • Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.

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: Can this dataset be used for logistics planning?

A: Yes. Many customers use these datasets to optimize delivery territories, distribution networks, route planning, and last-mile logistics analysis.

Q: Is this dataset suitable for market analysis?

A: Yes. The dataset is designed for retail analysis, competitor benchmarking, site selection, market coverage studies, and geospatial intelligence workflows.

Q: How are addresses standardized?

A: Addresses are cleaned and normalized through automated formatting and validation workflows to improve consistency and usability.

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 preview the dataset before purchasing?

A: Yes. A free sample is available so you can evaluate the structure, fields, and geospatial quality before purchase.

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: Is this dataset useful for franchise analysis?

A: Yes. The dataset can support franchise territory planning, network expansion analysis, and regional performance benchmarking.

Analyze this data with AI

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

  • "Analyze this Konsum dataset to identify underserved regions in Germany for potential market expansion."
  • "Map the concentration of Konsum locations relative to major retail centers and shopping districts in Germany."
  • "Identify the most central Konsum locations in Germany to serve as hubs for a last-mile delivery network."

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.