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Mitsubishi Dealers Locations Dataset | South Africa

Mitsubishi Dealers location data for South Africa, collected directly from the brand's official store locator and validated by Vaslap. A complete, geocoded list of 52 Mitsubishi Dealers points nationwide with coordinates, addresses, provinces and contact details, structured for GIS, retail analytics, site selection and AI/RAG workflows.

There are 52 locations in this dataset as of 7 August 2026. Compiled and maintained by Vaslap, complete, geocoded and structured for GIS, retail analytics, mapping and AI/RAG workflows.

Get answers like· How many Mitsubishi Dealers outlets per province?· Where does Mitsubishi Dealers cluster, and where is it absent?· Which towns has Mitsubishi Dealers not entered yet?· Verified Mitsubishi Dealers contact list for outreach

01 /Geographic distribution

Store distribution across South Africa
52 verified locations · 9 of 9 provincesExact coordinates in the full dataset

Preview shows true store positions as a static, watermarked image. The purchased CSV contains exact WGS84 coordinates for all 52 locations.

02 /Dataset summary

Coverage
52 locations, South Africa
Contents
Coordinates, addresses, provinces, phone numbers, ratings, source URLs
File format
Fully geocoded CSV (UTF-8); GeoJSON / Shapefile / Excel on request
Free sample
Instant download to verify structure and quality
Use cases
GIS, retail analytics, site selection, AI/RAG workflows
Last updated
7 August 2026

03 /Methodology

This dataset is compiled from publicly available business listings using systematic, grid-based collection that covers every province of South Africa, followed by geospatial validation workflows. Automated quality checks and manual analyst reviews are applied to improve coordinate precision, address standardisation, duplicate detection and overall analytical consistency.

Brand attribution is performed by normalising trading names against known retail chain and buying-group identities. Province attribution is derived from each record's verified WGS84 coordinates.

The dataset is periodically reviewed and refreshed to reflect known network changes, new openings, closures and relocations.

04 /Fields included in the CSV

GUIDStable unique identifier for each location record
TitleTrading name of the store as listed publicly
BrandDetected retail chain or buying group (blank for independents)
CategoryBusiness category (e.g. Hardware store, Building materials supplier)
LatitudeWGS84 latitude, 7-decimal precision
LongitudeWGS84 longitude, 7-decimal precision
AddressStreet address as published on the public listing
ProvinceSouth African province, derived from coordinates
PhonePublished contact number where available
Google RatingPublic review rating (0 to 5) where available
Review CountNumber of public reviews where available
Google Maps URLSource listing URL for verification
Last VerifiedDate the record was last collected and validated

05 /Data quality scorecard

Geospatial accuracy (verified WGS84 coordinates)100%
Contact details (phone)100%
Street address100%
Google rating0%

06 /Data preview

IDTitleLatitudeLongitudeProvinceAddress
0c14b382Ballito Showroom-29.52783631.198149KwaZulu-NatalUnit 3, Rekha Park, Garlick Drive, Ballito
a1b5a998Bedfordview-26.17731128.120795Gauteng2 Viscount Road, Bedfordview
5f0e77d3Bethlehem-28.23548728.306605Free State182 Commissioner Street, Bethlehem
da9f999fBloemfontein-29.11335726.221542Free StateCnr Zastron and Westburger Street
0978105dBronkhorstspruit-25.80924828.748322GautengCnr Botha & Burger streets
9cbb0058Bryanston-26.07417528.013316Gauteng282 Main road
622b2597Centurion-25.87185428.194965Gauteng1088 John Vorster drive, Highveld, Centurion, 0157
26925a10Clearwater-26.13315527.914364GautengCnr Hendrik Potgieter & Jim Fouche Road, Roodepoort

Only a subset of fields is displayed here. Download the free sample to view all fields and verify the structure.

07 /Provincial distribution

Gauteng
14
KwaZulu-Natal
11
Western Cape
7
Mpumalanga
7
Free State
3
North West
3
Eastern Cape
3
Limpopo
2
Northern Cape
2

08 /Who uses this data

01 /

Site selection & network planning

Identify under-served towns and whitespace across this brand network. Outcome: smarter expansion

02 /

Competitive benchmarking

Compare store footprints, regional density and market presence. Outcome: no blind spots

03 /

B2B sales & telemarketing

Pitch POS, insurance, cleaning, security and logistics to verified store contacts. Outcome: bigger pipeline

04 /

CRM enrichment

Append standardised coordinates and contact details to Salesforce or HubSpot records. Outcome: cleaner data

05 /

Trade-area & mobility analysis

Evaluate retail proximity to transport corridors and residential growth nodes. Outcome: defensible catchments

06 /

Geofencing & local advertising

Build hyper-local campaigns around store catchments. Outcome: sharper targeting

09 /Frequently asked questions

What file format is included with the download?

The dataset is delivered as a UTF-8 CSV file compatible with Excel, Python, R, QGIS, Power BI, Tableau and PostgreSQL, as well as most GIS and analytics platforms. GeoJSON, Shapefile and Excel delivery are available on request.

How accurate are the coordinates?

Every record carries WGS84 coordinates captured from the source listing and passed through automated validation and manual quality review. Coordinates are suitable for mapping, territory planning and drive-time analysis.

Is the dataset standardised for analytics workflows?

Yes. Field naming, address formatting, brand attribution and province tagging are standardised so the file drops cleanly into BI tools, GIS software and data pipelines without cleaning.

Can this dataset support expansion planning?

Yes. Analysts use it to identify under-served areas, evaluate regional density and benchmark candidate sites against existing store networks.

How often is the data updated?

This dataset was last refreshed on 2026-08-07 and is reviewed on a quarterly cycle. Purchases include the current snapshot; refresh subscriptions are available on request.

Can I get the data for a different industry or region?

Yes. Vaslap builds custom datasets on request, any retail category, brand set or region of South Africa. Use the custom-dataset form and we will scope it with you.

10 /Analyse this data with AI

Use these prompts with ChatGPT, Claude or Gemini once you have the CSV:

Analyse this Mitsubishi Dealers Locations dataset to identify under-served provinces in South Africa for potential market expansion.
Assess how effectively the current store network in this Mitsubishi Dealers Locations dataset covers major commercial and residential hubs.
Rank South African towns by hardware retail saturation using this dataset and highlight the top 10 whitespace opportunities.

Disclaimer: All brand names and trademarks are the property of their respective owners and are used strictly for identification purposes. This product consists of geospatial location data compiled from public sources; no logos, images or trademark rights are included.

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