SKU: 41951115765

SPAR Supermarket Locations Dataset – Netherlands

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Description

SPAR Supermarket Locations Dataset – NetherlandsQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI SPAR in the Netherlands operates various formats, including neighborhood supermarkets, city stores (City), and university based outlets (Express). It focuses on convenience and proximity, catering to the needs of modern, urban Dutch consumers. There are 454 SPAR Supermarkets as of 26 May 2026 in the

SPAR in the Netherlands operates various formats, including neighborhood supermarkets, city stores (City), and university-based outlets (Express). It focuses on convenience and proximity, catering to the needs of modern, urban Dutch consumers.

There are 454 SPAR Supermarkets as of 26 May 2026 in the Netherlands. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all SPAR 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: 454 SPAR supermarkets in the Netherlands
  • 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: 26 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
  • City
  • Admin_level_1
  • Admin_level_2
  • Settlement
  • Region
  • Population
  • Postal Code
  • Address
  • Wheelchair
  • Popularity Score
  • Phone
  • Website
  • Opening hours

Data Quality Scorecard

  • Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
  • Contact Details (Phone)95%
  • Web Address97%
  • Opening Hours97%
  • Popularity Score100%

Data Preview: Sample geospatial records from the SPAR dataset in Netherlands

ID Location Title Latitude Longitude Postal Code Full Address
25c5837... SPAR (Geesteren) 52.138915 6.525889 7274 AM 9 Dorpsstraat, Geesteren, 7274 AM, Be...
99baad5... SPAR express (Hilversum) 52.233559 5.176034 1211 AD 80 Lage Naarderweg, Hilversum, 1211 A...
728ffa4... SPAR (Ooij) 51.855680 5.938358 6576 BT 23 Reiner van Ooiplein, Ooij, 6576 BT...
47189d9... SPAR express (Nieuwerkerk aan den IJssel) 51.967458 4.599497 2912 TD 2 Europalaan, Nieuwerkerk aan den IJs...
e13eeca... SPAR (Genderen) 51.737786 5.089753 4265 HJ 37 Hoofdstraat, Genderen, 4265 HJ, Al...

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 26 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 SPAR locations in the Netherlands is found in Gelderland (73 sites, equivalent to 3.38 SPAR supermarkets per 100,000 residents). This is followed by Zuid-Holland (73 sites; 1.89 per 100,000) and Noord-Holland (72 sites; 2.41 per 100,000). From a market-penetration perspective, Zeeland has the highest brand density at 6.15 locations per 100,000 people (population: 390,000), making it the most saturated region for SPAR in the Netherlands. By contrast, Utrecht records only 1.85 locations per 100,000 residents (population: 1,405,000), 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 the Netherlands

Brand bundle

Top 16 Grocery Brands in the Netherlands — €250

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 the Netherlands — 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?

  • Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
  • Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
  • 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.
  • Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
  • Store Closure & Relocation Strategy: Corporate teams optimizing existing footprints by analyzing underperforming regions.
  • Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
  • Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.

Frequently Asked Questions

Q: Can I use this dataset in GIS software?

A: Yes. The dataset is suitable for GIS platforms including QGIS, ArcGIS, GeoPandas, CARTO, and other spatial analysis environments.

Q: Is this dataset useful for franchise analysis?

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

Q: Can I combine this dataset with administrative boundaries?

A: Yes. The coordinates can be spatially joined with municipalities, census units, postal areas, and other administrative polygons.

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: Does the dataset include unique identifiers?

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

Q: Can this dataset support territory optimization?

A: Yes. The dataset is suitable for defining service territories, balancing regional coverage, and optimizing operational footprints.

Q: Does the dataset include opening hours?

A: Yes, opening hours are included where publicly available and validated during the data standardization process.

Q: Can I use this dataset for proximity analysis?

A: Yes. The geocoded coordinates are suitable for drive-time analysis, catchment modeling, nearest-neighbor analysis, and accessibility studies.

Analyze this data with AI

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

  • "Analyze this SPAR dataset to identify underserved regions in the Netherlands for potential market expansion."
  • "Identify locations where multiple SPAR sites compete within overlapping catchment areas in the Netherlands."
  • "Analyze the clustering behavior of SPAR locations to determine whether the network prioritizes convenience, coverage, or saturation strategies."

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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