Vaslap

Hardware Stores Locations Dataset | South Africa

The complete, geocoded directory of hardware stores, building-materials suppliers and home-improvement retailers across South Africa , national chains, buying-group members and independent stores. Compiled and maintained by Vaslap from public business listings with geospatial validation. Built for GIS, retail analytics, site selection, competitive benchmarking and AI/RAG workflows.

There are 6,507 locations in this dataset as of 27 July 2026. Compiled and maintained by Vaslap, complete, geocoded and structured for GIS, retail analytics, mapping and AI/RAG workflows.

Get answers like· Outlet count per chain, by province· Where competitors cluster, and where they are absent· Whitespace towns no major chain serves yet· Head-to-head footprint overlap between rivals

01 /Geographic distribution

Store distribution across South Africa
6,507 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 6,507 locations.

02 /Dataset summary

Coverage
6,507 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
27 July 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)88%
Street address80%
Google rating89%

06 /Data preview

IDTitleLatitudeLongitudeProvinceAddress
e1dcab1eCasteel Hardware-24.72038531.023225Mpumalanga
e6cbbfdbRAJA HARDWARE-24.60100231.044261MpumalangaR40 North
04b7a496Laduma Hardware Thulamahashe-24.72419431.212370MpumalangaRolle Road Opposite Thula Mall
15890730BUCO Acornhoek-24.60653131.037466MpumalangaTrust Farm, R40
8f538efcCashbuild Casteel-24.71012531.026461MpumalangaR40
1556d6b2Laduma Hardware Acornhoek-24.59705331.057105Mpumalanga
5a5bb317Build it Thulamahashe-24.72277231.210976MpumalangaKumani Rd Thulamahashe Mall
5c02df6cAcornhoek Hardware cc-24.59940131.050610MpumalangaShop 8, Mega City/ Plaza, Main Road

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

07 /Provincial distribution

Gauteng
1,720
KwaZulu-Natal
1,109
Limpopo
936
Eastern Cape
874
Mpumalanga
550
Western Cape
531
North West
403
Free State
288
Northern Cape
96

08 /Who uses this data

01 /

Site selection & network planning

Identify under-served towns and whitespace across the retail landscape. 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 2026-07-27 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 Hardware Stores Locations dataset to identify under-served provinces in South Africa for potential market expansion.
Assess how effectively the current store network in this Hardware Stores 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.

Related datasets