Vaslap

Every retail location in South Africa. Mapped. Verified. Downloadable.

Complete store footprints for 64 South African retail chains, every outlet with GPS coordinates, address and contact details. Track competitors, find whitespace and size markets with data that drops straight into your GIS, BI or AI stack.

Locations mapped
25,610
Retail brands
64
Provinces covered
9 / 9
Map of 25,610 verified retail store locations across South Africa's nine provinces

Every dot is a real, geocoded store position in the Vaslap database.

Get answers like· Outlet count per chain, by province or metro· Where competitors cluster, and where they are absent· Which towns a chain has not entered yet· Head-to-head footprint overlap between rival brands· Verified contact lists for localized B2B outreach

Featured datasets

Analysis-ready CSV downloads with a free 10-row sample on every product.

View all 61 datasets →
Absa Locations Dataset | South Africa store distribution map
Brand datasetR549

Absa Locations Dataset | South Africa

Absa location data for South Africa, collected directly from the brand's official store locator and validated by Vaslap. A complete, geocoded list of 4,800 Absa points nationwide with coordinates, addresses, provinces and contact details, structured for GIS, retail analytics, site selection and AI/RAG workflows.

4,799 recordsUpdated 7 August 2026
Standard Bank Locations Dataset | South Africa store distribution map
Brand datasetR549

Standard Bank Locations Dataset | South Africa

Standard Bank location data for South Africa, collected directly from the brand's official store locator and validated by Vaslap. A complete, geocoded list of 2,389 Standard Bank points nationwide with coordinates, addresses, provinces and contact details, structured for GIS, retail analytics, site selection and AI/RAG workflows.

2,351 recordsUpdated 7 August 2026
Spar Locations Dataset | South Africa store distribution map
Brand datasetR549

Spar Locations Dataset | South Africa

Spar location data for South Africa, collected directly from the brand's official store locator and validated by Vaslap. A complete, geocoded list of 1,503 Spar points nationwide with coordinates, addresses, provinces and contact details, structured for GIS, retail analytics, site selection and AI/RAG workflows.

1,401 recordsUpdated 7 August 2026
Astron Energy Locations Dataset | South Africa store distribution map
Brand datasetR449

Astron Energy Locations Dataset | South Africa

Astron Energy location data for South Africa, collected directly from the brand's official store locator and validated by Vaslap. A complete, geocoded list of 781 Astron Energy points nationwide with coordinates, addresses, provinces and contact details, structured for GIS, retail analytics, site selection and AI/RAG workflows.

781 recordsUpdated 7 August 2026
Debonairs Pizza Locations Dataset | South Africa store distribution map
Brand datasetR449

Debonairs Pizza Locations Dataset | South Africa

Debonairs Pizza location data for South Africa, collected directly from the brand's official store locator and validated by Vaslap. A complete, geocoded list of 772 Debonairs Pizza points nationwide with coordinates, addresses, provinces and contact details, structured for GIS, retail analytics, site selection and AI/RAG workflows.

761 recordsUpdated 7 August 2026
Steers Locations Dataset | South Africa store distribution map
Brand datasetR449

Steers Locations Dataset | South Africa

Steers location data for South Africa, collected directly from the brand's official store locator and validated by Vaslap. A complete, geocoded list of 694 Steers points nationwide with coordinates, addresses, provinces and contact details, structured for GIS, retail analytics, site selection and AI/RAG workflows.

681 recordsUpdated 7 August 2026

Why teams choose Vaslap

01 /

GPS-verified positions

Every location carries an exact WGS84 coordinate, validated against official store locators and map sources, not approximated from addresses.

02 /

Geo-ready formats

UTF-8 CSV by default, GeoJSON, Shapefile, Excel or database loads on request. Drops straight into QGIS, ArcGIS, Power BI, Tableau and Python.

03 /

Always growing

The database is refreshed on a rolling cycle and new brands are added every week. Counts on this site are live, not marketing numbers.

04 /

Compliant sourcing

Compiled exclusively from publicly available sources. Procurement-ready, with VAT invoices and clear licensing.

05 /

Any scope

License a single brand, a chain bundle, a full category or a custom cut by region. Pricing scales to what you actually need.

06 /

Free sample first

Every dataset ships with a free 10-row sample so you can validate structure and quality before you spend a cent.

Coverage by retail category

From grocery and fast food to banking, fuel and furniture, explore store-location data for every major South African retail sector.

Built for retail-focused decision-makers

Retailers & franchise teams

Network planning, territory design, cannibalization checks and whitespace analysis before your next site.

Property, brokers & lenders

Anchor-tenant proximity, trade-area validation and covenant risk, backed by defensible location data.

Investors & analysts

Model chain growth and market structure from real footprint data instead of annual-report estimates.

Suppliers & B2B sales

Target chains by outlet count and geography with verified store contact lists that fill pipeline.

Government & researchers

Track commercial density, township retail formalization and spatial economics across all nine provinces.

Consultants & agencies

Standardised, citation-ready location data that makes client deliverables faster and more credible.

Brands we map

National chains, franchises and buying groups, verified from official store locators.

All 64 brands →
Absa store locations datasetStandard Bank store locations datasetSpar store locations datasetAstron Energy store locations datasetDebonairs Pizza store locations datasetSteers store locations datasetRage Shoes store locations datasetVodacom store locations datasetWimpy store locations datasetVida e Caffè store locations datasetTelkom store locations datasetBuild it store locations datasetMugg & Bean store locations datasetOK Furniture store locations datasetNando's store locations datasetChicken Licken store locations datasetThe Local Choice Pharmacy store locations datasetBuilders store locations dataset

How it works

1

Pick your dataset

Choose a brand, a chain bundle, or full-market category coverage. Every product page shows a live distribution map, field list, quality scorecard and a free sample.

2

Request & pay securely

Request the dataset, receive a VAT invoice, and get a secure download link as soon as payment confirms. EFT and card supported.

3

Plug into your stack

Clean, standardised UTF-8 CSV that drops straight into Excel, Python, QGIS, Power BI, Tableau or PostgreSQL. GeoJSON and Shapefile on request.

Frequently asked questions

What is a store location dataset?

A structured CSV file containing every verified store, branch or dealership of a retail brand or category in South Africa, with exact WGS84 coordinates, street addresses, provinces, phone numbers and ratings. Ready for Excel, QGIS, Power BI, Python and AI workflows.

Which South African retail brands are covered?

We currently map 64 national chains and buying groups across grocery, fast food, banking, fuel, furniture, pharmacy, automotive, clothing, hardware and more, with new brands added in every collection cycle.

How current is the data?

Datasets are refreshed directly from official brand store locators and verified public sources on a rolling cycle. Every product page shows its last-updated date, and all counts on this site are read live from the database.

Can I get data in GeoJSON, Shapefile or Excel?

Yes. Every dataset ships as UTF-8 CSV by default, and we deliver GeoJSON, Shapefile, Excel or direct database loads on request at no extra cost.

Need a brand or category we don't list yet?

We map custom datasets on request: any retail category, brand set or region in South Africa, typically within days.

Request a custom dataset