GigaCharger EV Charging Station Locations Dataset – Bulgaria

GigaCharger EV Charging Station Locations Dataset – BulgariaQuick links: Dataset Summary Methodology Download Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI GigaCharger is a Bulgarian EV charging network that manufactures its own low cost charging stations domestically, placing them at public locations, homes, hotels, business parks, and other venues, with the aim of offering some of the lowest charging costs available. There are 419 GigaCharger EV Charging Stations as of 2

GigaCharger is a Bulgarian EV charging network that manufactures its own low-cost charging stations domestically, placing them at public locations, homes, hotels, business parks, and other venues, with the aim of offering some of the lowest charging costs available.

There are 419 GigaCharger EV Charging Stations as of 2 June 2026 in Bulgaria. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all GigaCharger 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 Preview: Sample geospatial records from the GigaCharger dataset in Bulgaria

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of GigaCharger locations in Bulgaria is found in София-Град (114 sites, equivalent to 8.8 GigaCharger ev charging stations per 100,000 residents). This is followed by Варна (90 sites; 20.69 per 100,000) and Русе (49 sites; 26.49 per 100,000). From a market-penetration perspective, Русе has the highest brand density at 26.49 locations per 100,000 people (population: 185,000), making it the most saturated region for GigaCharger in Bulgaria. By contrast, Хасково records only 0.98 locations per 100,000 residents (population: 205,000), indicating a potential white-space opportunity for network expansion or competitor analysis.

Also available for Bulgaria

Related geospatial datasets

• Administrative boundaries and full polygon dataset for Bulgaria: Map these GigaCharger 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 GigaCharger 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 [email protected].

Who uses this data?

• 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.
• Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
• B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
• CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
• 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.
• 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.

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 GigaCharger dataset to identify underserved regions in Bulgaria for potential market expansion."
• "Assess how effectively the current GigaCharger network covers major commercial and residential hubs across Bulgaria."
• "Evaluate how evenly GigaCharger locations are distributed across provinces, districts, or municipalities in Bulgaria."

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.