Burlex Supermarket Locations Dataset – Bulgaria

Burlex

There are 68 Burlex Supermarkets as of 27 August 2026 in Bulgaria. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Burlex 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 Burlex dataset in Bulgaria

ID	Location Title	Latitude	Longitude	Postal Code	Full Address
868b9a2...	8255 магазин Бурлекс 2	42.670828	23.599322	2100	Unnamed Road, Elin Pelin, 2100, Bulgaria
3a59d15...	Burlex	43.210172	27.924028	9002	4 ulitsa "Vasil Drumev", Varna, 9002,...
adba929...	Бурлекс Балчик	43.425027	28.162770	9601	1 ulitsa "Cherno More", Balchik, 9601...
d9f2ad7...	Burlex	43.232318	27.885590	9020	129А 2 zh.k. Mladost II, Varna, 9020,...
58e3361...	Бурлекс Габрово Хали	42.873659	25.318862	5300	18 ulitsa "General Radetski", Gabrovo...

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 Burlex locations in Bulgaria is found in Варна (32 sites, equivalent to 7.36 Burlex supermarkets per 100,000 residents). This is followed by София-Град (17 sites; 1.31 per 100,000) and Русе (6 sites; 3.24 per 100,000). From a market-penetration perspective, Варна has the highest brand density at 7.36 locations per 100,000 people (population: 435,000), making it the most saturated region for Burlex in Bulgaria. By contrast, Шумен records only 0.69 locations per 100,000 residents (population: 145,000), 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 Bulgaria

Related geospatial datasets

• Administrative boundaries and full polygon dataset for Bulgaria: Map these Burlex locations against highly precise administrative polygons for territory analysis and spatial structuring.
• Demographics dataset for Bulgaria: Overlay demographic indicators to deeply understand the population structures and household types surrounding these Burlex locations.
• Explore demographics data insights for Bulgaria: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
• Income indicators dataset for Bulgaria (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.
• Income distribution and socio-economic patterns in Bulgaria - expert analysis: A detailed blog post explaining income geography, disparities, and how income-based indicators can support location intelligence and market analytics.
• Explore a rich library of Bulgaria-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 Bulgaria

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.
• Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
• Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
• Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
• Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
• Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.

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 Burlex dataset to identify underserved regions in Bulgaria for potential market expansion."
• "Identify isolated Burlex sites in Bulgaria that may face operational inefficiencies due to low regional clustering."
• "Using this Burlex data, find high-traffic retail corridors in Bulgaria with low supermarkets density for competitive positioning."

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.