Independent property market intelligence
SuburbScanner is a residential market screening platform for Australian property investors. It applies a consistent, multi-factor research model across 34+ markets — yield, vacancy, rent momentum, policy exposure, and market discovery status — updated monthly. No agent advertising. No commercial data provider attribution on public pages. No financial advice.
Why it exists
Property research in Australia has a structural problem: the sources most investors rely on are commercially conflicted. Portal research is funded by agent advertising. Vendor-commissioned reports optimise for optimism. Institutional research — JLL, CBRE, CoreLogic subscriptions — is accurate and rigorous, but priced at five-figure annual fees for institutional buyers and developers. It does not cover the long tail of regional and secondary markets where most individual investors actually operate.
SuburbScanner was built to address that gap. The platform applies the same screening methodology across all covered markets — coastal, regional, mining-adjacent, agricultural — in a format accessible to individual investors, not just institutions.
The core thesis: property markets in Australia are relatively efficient at the transaction layer (price discovery converges quickly in most markets). They are less efficient at the information layer — particularly in markets that institutional research does not cover and that consumer portals treat as lifestyle guides rather than investment research objects.
Founder
Richard has a background in structured finance and credit analysis. His professional experience spans debt structuring, credit assessment, and financial modelling — work that requires the same systematic, data-first approach that underpins SuburbScanner's research methodology.
SuburbScanner emerged from the frustration of trying to research Australian property markets rigorously using publicly available tools and finding that the available research was either commercially conflicted, restricted to capital city markets, or inaccessible to individual investors.
The platform is built and maintained independently, without external investment or commercial property industry partnerships.
Platform philosophy
SuburbScanner has no affiliation with real estate agents, property developers, mortgage brokers, or commercial data providers. There is no agent advertising on the platform. Research signals are not influenced by listing revenue or vendor relationships.
Institutional property research is accurate and deep — but priced for institutional buyers. Consumer portals are accessible — but commercially conflicted by agent advertising. SuburbScanner occupies the gap: research-grade screening methodology at a price point accessible to individual investors.
The scoring model is documented in the methodology page. Factor weights, thresholds, and update cadence are transparent. The platform does not use AI-generated suburb narratives or LLM-produced research copy — those outputs are not proprietary and erode research credibility.
All data inputs are documented internally with named fallback sources. No single commercial provider is load-bearing. If any source changes pricing or access policy, the platform has identified alternative sources for each metric.
Current scope
What's being built
The current platform is a screening and comparison tool. The near-term priority is adding temporal depth — score history per suburb across batches, enabling trend analysis ("this market moved from score 51 to 68 over three batches") rather than just a point-in-time snapshot.
Subsequent builds include watchlists (save a suburb and receive alerts when a material change is detected), multi-lens scoring profiles (yield-first, cashflow, growth, defensive), and expanded coverage into markets that institutional research does not currently cover.
The build sequence is disciplined: each layer depends on the one below it. Score history before watchlists. Watchlists before alerts. Alerts before multi-lens profiles. No feature ships before its infrastructure is solid.
Research model
The scoring model is documented in full on the methodology page. The short version: a multi-factor composite across seven dimensions — rental yield, rent growth, price-to-rent spread, supply tightness (vacancy), employment fundamentals, market liquidity, and discovery status (a penalty for already-crowded media coverage).
Scores are dataset-relative — they describe a suburb's position in the current covered dataset, not an absolute investment quality rating. A high score in a 34-market dataset does not mean the same thing as a high score in a 200-market dataset. This is intentional: the model is calibrated to the current coverage universe.
Read the full methodology →Get in touch
Reach out via LinkedIn for research enquiries, data contributions, or partnership discussions. Structured finance professionals, property researchers, and state real estate body representatives are particularly welcome to connect regarding data sourcing and methodology.
Connect on LinkedIn →SuburbScanner is operated by Florentino Ventures Pty Ltd (ABN 24 698 300 917). All content is general information only and does not constitute financial, investment, tax, or legal advice. SuburbScanner does not hold an Australian Financial Services Licence (AFSL). Do not rely on Scanner Scores or any content on this platform as the basis for investment decisions. Seek independent financial and legal advice before making any property investment.