Methodology
How StreetSignal works
StreetSignal is a structured data platform. Every number on this site is traceable to a primary South African government source. This page explains exactly how we collect, process, and present that data, and where the gaps and limitations are.
The problem we're solving
South African property markets exhibit high information asymmetry, not because data doesn't exist, but because transaction records, municipal valuations, safety statistics, and infrastructure data are fragmented across different government systems, published in incompatible formats, and updated on different schedules.
Analytics-ready suburb intelligence is typically siloed within private commercial providers, estate agents, banks, data brokers, and sold back to citizens as PDF reports or gated behind agent networks. The person buying a home ends up with less information than the person selling it.
Cape Town is the pilot city because the City operates one of the most mature open data ecosystems in Africa. That foundation makes it possible to build something verifiable: a platform where every data point has an auditable source.
The South African context
In Cape Town, suburb boundaries carry durable economic meaning that has no equivalent in most Western cities. The Group Areas Act (1950-1991) engineered racially segregated urban spaces using highways, railway lines, and buffer strips as physical barriers. Those barriers remain intact today. Post-apartheid housing programmes delivered shelter on the urban periphery but not spatial access to employment, transport, or services.
This means that neighbourhood-level data in Cape Town is not neutral. Property values, crime rates, school outcomes, and service delivery indices all reflect a spatial inheritance that concentrates resources in historically white suburbs and under-invests in historically black and coloured communities. Any platform presenting this data without naming that structural context risks reinforcing the patterns it claims to describe.
How StreetSignal responds
- Every index is relative to the current city, not absolute. A safety index of 70 means safer than approximately 70% of suburbs in that city - not safe in any universal sense.
- Where a suburb's data reflects structural under-investment, the page names the cause rather than presenting it as a community characteristic.
- Challenges are always presented alongside strengths. No suburb page shows only negative indicators.
- Trend direction is surfaced wherever available, because trajectory matters more than a single snapshot.
- Language follows asset-based framing principles: "food insecurity prevalence" not "hunger rate", "grant income share" not "grant dependency".
Methodology sections
Data Sources
The 14 datasets from 9 government sources that StreetSignal ingests and what we compute from each one -- property valuations, crime statistics, education, transport, infrastructure, and more.
Safety Index
How the safety index is computed in five steps, risk band thresholds, the tourist precinct paradox, suppressed scores, crime volume handling, trend assessment, and data confidence tiers.
Indices and Features
Service Delivery Index, Development Focus Areas, New Development Areas, free basic electricity, neighbourhood narratives, comparison pages, and change detection.
Governance and Limitations
Where AI is and is not involved, 13 known data limitations, data freshness schedule, and responsible use policy.
Questions about our methodology or data sources? Contact us at [email protected]. Full attribution and licence details are on our Attribution & Copyright page. This platform is not a substitute for professional property, legal, or safety advice.