SKU: 84330167020

SPAR Supermarket Locations Dataset – Hungary

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Description

SPAR Supermarket Locations Dataset – HungaryQuick links: Dataset Summary Methodology Download Data Quality Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI SPAR is a major player in the Hungarian grocery sector, operating a diverse range of formats from small convenience stores to large INTERSPAR hypermarkets. It is well regarded for its high quality meat and deli departments, often sourced from its own regional production sites. There are 658 SPAR Supermarkets

SPAR is a major player in the Hungarian grocery sector, operating a diverse range of formats from small convenience stores to large INTERSPAR hypermarkets. It is well-regarded for its high-quality meat and deli departments, often sourced from its own regional production sites.

There are 658 SPAR Supermarkets as of 29 May 2026 in Hungary. 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: 658 SPAR supermarkets in Hungary
  • 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: 29 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
  • Municipality
  • Region
  • Population
  • Postal Code
  • Address
  • Wheelchair
  • Popularity Score
  • Phone
  • Website
  • Opening hours

Data Quality Scorecard

  • Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
  • Contact Details (Phone)81%
  • Web Address88%
  • Opening Hours90%
  • Popularity Score100%

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

ID Location Title Latitude Longitude Postal Code Full Address
094a79e... SPAR partner (Taksony) 47.335389 19.065533 2335 10 Szent István tér, Taksony, 2335, H...
96c40e7... SPAR (IV. kerület) 47.586775 19.112653 1048 12 Kordován tér, Budapest, 1048, Hungary
3ead925... SPAR market (Zomba) 46.411534 18.565572 7173 2 Rákóczi utca, Zomba, 7173, Hungary
09d4871... SPAR (XVIII. kerület) 47.433024 19.178258 1182 15/b Cziffra György utca, Budapest, 1...
98d4d7f... DESPAR (Tárnok) 47.356661 18.809052 2461 M7, Tárnok, 2461, Hungary

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 29 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 Hungary is found in Közép-Magyarország (255 sites, equivalent to 8.44 SPAR supermarkets per 100,000 residents). This is followed by Közép-Dunántúl (89 sites; 8.48 per 100,000) and Nyugat-Dunántúl (78 sites; 8.04 per 100,000). From a market-penetration perspective, Közép-Dunántúl has the highest brand density at 8.48 locations per 100,000 people (population: 1,050,000), making it the most saturated region for SPAR in Hungary. By contrast, Észak-Alföld records only 4.1 locations per 100,000 residents (population: 1,390,000), indicating a potential white-space opportunity for network expansion or competitor analysis.

Also available for Hungary

Brand bundle

Top 8 Grocery Brands in Hungary - €175

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 Hungary - 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?

  • Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
  • Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
  • B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
  • Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
  • Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
  • Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
  • Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.

Frequently Asked Questions

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: 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.

Q: Does the dataset include opening hours?

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

Q: Are phone numbers and websites included?

A: Yes. Where available, the dataset includes standardized phone numbers and official website URLs.

Q: Are postal codes included for all locations?

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

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 Hungary for potential market expansion."
  • "Identify fast-growing suburban areas in Hungary that currently have limited access to nearby supermarkets."
  • "Identify regions in Hungary where SPAR has a disproportionately strong or weak presence relative to population density."

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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SKU: 84330167020

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