HOL'AB! Supermarket Locations Dataset – Germany

HOL'AB! Supermarket Locations Dataset – GermanyQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI HOL'AB! is a specialized beverage retail chain operating primarily in Northern Germany. It offers an extensive portfolio of international and regional beverages, catering to both private households and events. There are 159 HOL'AB! Supermarkets as of 27 May 2026 in Germany. This dataset is compiled and

HOL'AB! is a specialized beverage retail chain operating primarily in Northern Germany. It offers an extensive portfolio of international and regional beverages, catering to both private households and events.

There are 159 HOL'AB! Supermarkets as of 27 May 2026 in Germany. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all HOL'AB! 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 HOL'AB! dataset in 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.

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of HOL'AB! locations in Germany is found in Niedersachsen (127 sites, equivalent to 1.58 HOL'AB! supermarkets per 100,000 residents). This is followed by Bremen (19 sites; 2.81 per 100,000) and Hamburg (4 sites; 0.22 per 100,000). From a market-penetration perspective, Bremen has the highest brand density at 2.81 locations per 100,000 people (population: 675,000), making it the most saturated region for HOL'AB! in Germany. By contrast, Nordrhein-Westfalen records only 0.02 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

Related geospatial datasets

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

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?

• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
• Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
• Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
• Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
• Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
• Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
• Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
• Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
• B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
• Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.

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 HOL'AB! dataset to identify underserved regions in Germany for potential market expansion."
• "Create a regional ranking of HOL'AB! coverage efficiency using population-to-store ratios across Germany."
• "Analyze which HOL'AB! locations in Germany are positioned in highly competitive retail zones versus standalone markets."

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.