Microburbs fuses 633 property attributes, 5,182 suburb fields, and 473 government datasets onto every one of Australia's roughly 16 million addresses. Whether you need a franchise territory drawn around a true demand surface, a polling booth model that explains why working-class Labor voters voted No, or a forecast of who is most likely to switch to an EV, we already hold the data and the modelling pipelines. You bring the question.
Most place-data vendors operate at suburb or local-government level. Microburbs operates one to two levels finer. The 14% price gap we routinely observe between neighbouring streets in the same suburb in the same year is the clearest proof that the resolution matters, and that the questions worth answering are address-level, not suburb-level.
Every one of Australia's roughly 16 million GNAF addresses linked to its street, mesh block, SA1, SA2, SA3, SA4, postcode, LGA, SUA and the whole country. 350,000 mesh blocks scored across eight livability dimensions and tens of thousands of features each.
11.87 million paired property holds, cleaned with twenty noise filters that reject bulk replicas, deposit-versus-settlement duplicates, and price-parsing errors. Underpins capital-growth, AVM, gentrification and forced-sale models.
Council minutes scraped and parsed across major LGAs. Listings, agents, builders. Cadastre, zoning, heritage. Satellite imagery and street-view computer vision. Demographics, schools, NAPLAN, crime, climate peril, slope, terrain, NBN, infrastructure.
Capital-growth forecasts. Distressed-sale signals. Mortgage-stress index. Gentrification trajectory. House, unit and rental AVM. Internal benchmarking against actual outcomes since 2002.
Give Microburbs an address-level survey or label of any attribute, income, wellbeing, mobility, attitude, behaviour, and we can build a national propensity model off the FeatureStore. This is the single most important sentence on this page.
Every prediction ships with a sample data display, EDA, expert sanity check, confidence intervals, and a driver explanation written for a non-technical buyer. Methodologies have stood up to grant audits and bank credit committees.
The same FeatureStore that powers a property report powers a franchise territory map, a political booth analysis, an APRA climate vulnerability submission, and an aged-care site selection brief. Below is what we have built or prototyped for each sector.
The home-court sector. Twenty-five years of Australian property data, AVMs, repeat-sales registers, listings, agents, council pipelines, and microburb livability, all tuned for buyers' agents, developers, syndicators, REITs, valuers and asset managers.
Draw franchise territories around the demand surface, not the LGA boundary. Combine population, household income proxies, lifestyle, competitor coverage, drive-time and council-approved development pipelines to rank candidate sites and balance existing networks.
We model voting at polling-booth granularity using the same demographic, livability and economic features we use to model property markets. Past work explains why Labor's working class base voted No on the Voice, and why the educated and rich were most likely to vote Yes.
Microburb-level vulnerability indices, place-based program targeting, site selection for aged care, childcare, GP clinics, EV chargers and community hubs. Civic intelligence subscription for developers, regulators and NGOs.
House, unit and rental AVM with confidence intervals. Capital-growth forecasts at suburb, street and property level. Mortgage stress and forced-sale signals. Address-level climate vulnerability defensible to APRA.
Place-based health-needs assessments, aged-care and childcare demand, public housing need, financial inclusion gap maps, women's safety and domestic-violence prediction (where label data is available).
Address-level EV adoption propensity, rooftop solar uptake, climate peril, infrastructure deficit mapping. Built on dwelling type, off-street parking, household income proxies, electricity demand profile, neighbour adoption and charging access.
A working inventory of the FeatureStore. We measure what other vendors describe. Each category below is one slice of the data we already hold, ready to be joined to your label or your customer file.
The screenshots below come from one SA3, Chatswood-Lane Cove, with 1,521 mesh blocks. Multiplied across the country we hold tens of billions of feature observations, refreshed from the underlying datasets on a rolling basis.
Examples shown are from internal Microburbs builds. Available to consulting clients under NDA.
Browse a sample of the public field dictionary at microburbs.com.au/definitions. The full FeatureStore is available to consulting clients under NDA, including the 5,182 suburb fields, the 633 per-address attributes, and every join key needed to bring your own data alongside.
Microburbs Consulting and its predecessor Rapid Intelligence have delivered to commercial chains, healthcare providers and government clients. A selection where the work has been spoken about publicly is below.
Selected past and present clients of Microburbs and the Rapid Intelligence consulting practice. Many engagements are under NDA and are not listed.
The Physio Inq team brought Luke in to bring data-driven thinking to franchise growth and market modelling. The interview covers how the work shaped their decisions and what changed as a result.
Each line is something Microburbs has either delivered, prototyped, or has all the data plumbing to build inside a quarter. Engagements are scoped to the brief.
| # | Service line | What you get | Typical buyer |
|---|---|---|---|
| 1 | Address-level decision prediction | Train a propensity model at GNAF resolution for any binary or continuous decision a funder cares about. You bring the dependent variable, we bring the feature stack. | Federal departments, regulators, utilities, banks, insurers |
| 2 | Microburb mapping and vulnerability indices | Place-based mapping at mesh block level. Gentrification, deprivation, affluence, climate vulnerability, family stability, social cohesion. | Federal social services, state planning, councils, foundations, PHNs |
| 3 | Site selection and demand forecasting | Optimal locations for aged care, childcare, GP clinics, schools, EV chargers, retail, community hubs. | Health infrastructure, energy, retailers, councils |
| 4 | Place-based risk and resilience scoring | Microburb-level scoring across climate peril, crime trajectory, mortgage stress, tenancy churn, insurance peril. | APRA, ICA, NEMA, insurers, banks, emergency services |
| 5 | AVM and capital-growth disclosure | House, unit and rental valuations with confidence intervals. Defensible to bank credit committees and regulators. | Banks, regulators, developers, investors |
| 6 | Civic intelligence subscription | Structured feed from council minutes, planning decisions, builder commencement, heritage and zoning changes. | Developers, regulators, lobbyists, environmental NGOs |
| 7 | Custom national data layer | National layer of X at GNAF level delivered as parquet, CSV, API, or hosted dashboard. | ABS, AIHW, Geoscience Australia, AURIN, AHURI, large agencies |
| 8 | Behavioural CRM and program-uptake analytics | Direct port of the loyalty, churn and store-quality work delivered to commercial chains, applied to citizen-segment uptake and program retention. | Services Australia, BETA, DSS, utilities, NFP membership bodies |
| 9 | Whitepapers, disclosure and tender writing | Investor-grade whitepapers, methodology disclosures, landing pages and blog posts, sellable as a standalone capability. | Banks, insurers, regulators, consulting firms, applicant SMEs |
| 10 | Population mobility and migration analytics | Forecast internal migration, workforce shifts and demographic ageing at sub-LGA resolution. | State regional development, transport, NDIS demand planners |
| 11 | Computer vision on street-view and satellite | Public-housing detector already shipped. Extensible to amenity audits, building-condition scoring, vegetation cover, rooftop solar potential. | Social housing, urban planning, ABS, environment agencies |
| 12 | Embedded data scientist and co-design | Short-term secondment of the Microburbs team into your analytics function, with knowledge transfer and model handover. | Treasury, Health, Planning, ABS, large research institutions |
Concrete examples of the kind of product Microburbs ships, useful when a procurement officer asks what this would actually look like.
Filter every Australian property by AVM, growth forecast, yield, livability, zoning headroom, council pipeline pressure and any number of buyer-specific criteria. Outputs a ranked candidate list with a one-page brief per site.
Buyer: developers, buyers' agents, syndicators, family offices, BTR operatorsScan all-of-Australia for sites that match a brief: childcare-permissible parcels with 800+ kids in catchment, BTR-zoned land within 1 km of a station, last-mile logistics on industrial-zoned parcels with three-phase power, data-centre-grade lots with NBN-backbone proximity, medical-suite sites near established GP catchments.
Buyer: commercial developers, REITs, fund managers, healthcare and childcare operators, logisticsHeadline rent versus net effective rent, modelled across office, retail and industrial leases, accounting for rent-free periods, fit-out contributions, breaks and stepped reviews. Benchmarked at building, precinct and SA2 level.
Buyer: office and industrial REITs, valuers, leasing teams, tenant reps, property managersDaily or weekly digest of distress signals, bargain alerts, unusual listings, agent quoting anomalies, rezoning hits and council-pipeline movements that match a saved buyer brief. Delivered as email, Slack or pushed to CRM.
Buyer: buyers' agents, developers, investors, search firms, finance brokersFor every Australian address, the probability of EV adoption over the next 24 months. Inputs include dwelling type, off-street parking, household income proxies, electricity demand profile, neighbour adoption and charging access.
Buyer: Net Zero Authority, state energy departments, distributors, charger operatorsFor a national chain or franchise system, mesh-block-level demand scoring, territory recommendations, cannibalisation modelling and a development pipeline overlay scraped from council minutes. Delivered as interactive map, territory parquet and investor pack.
Buyer: franchise systems, retailers, healthcare networks, fitness chains, food and beverage groupsPer-booth predictions of two-party preferred and Yes/No vote, with SHAP-style driver attribution at SA1 level, in the language of demographics, livability and economic stress. Used to explain past results and target future campaigns.
Buyer: party strategists, candidates, lobby groups, journalists, academicsReal-time and 12-month-forward stress signal at mesh block level. Combines repayment-to-income proxy, listings churn, tenant turnover and distressed-sale precursors.
Buyer: RBA, APRA, ASIC, ATO, financial counsellors, banksProvider-facing tool combining birth rates, ageing-in-place propensity, supply pipeline and competitor coverage to rank candidate sites for new facilities.
Buyer: provider networks, Department of Health, Department of Education, foundationsStructured weekly digest of council minutes, planning decisions, builder activity, zoning and heritage changes.
Buyer: developers, lobbyists, environmental NGOs, materials suppliersFor every public-school catchment, demographic trajectory and 5-year enrolment forecast.
Buyer: education departments, PHNs, Catholic and independent networksAddress-level peril plus socioeconomic vulnerability for banks and insurers responding to APRA's Climate Vulnerability Assessment. Defensible methodology, audit trail, confidence intervals.
Buyer: APRA-regulated entities and the regulatorAutomated identification of public-amenity deficits, building-condition scoring, vegetation cover, by mesh block, using street-view computer vision. We have already shipped a public-housing detector built on this stack.
Buyer: state planning, social housing providers, ABS, environment agenciesEach is sourced from a published Microburbs research deliverable, with full methodology and data lineage available on request.
A selection of public Microburbs research projects. Each is a working demonstration of a capability we can rebuild for your jurisdiction, customer cohort or franchise network.
Per-booth modelling of how Australia voted, with demographic, economic and livability drivers identified at SA1.
View project → Civic intelligenceStructured signals from thousands of council meetings: rezoning, builder commencement, heritage and planning changes.
View project → RiskCombines repayment-to-income proxy, listings churn, tenant turnover and distressed-sale precursors.
View project → ForecastingAddress-level predictions back-tested against transactions since 2002.
View project → ValuationWhole-of-Australia automated valuation model, defensible to bank credit committees.
View project → ValuationPer-property rent estimates feeding yield and rental-stress modelling.
View project → RiskMesh-block crime modelling and its relationship to capital growth across the country.
View project → InfrastructureNational noise exposure layer over every address, fused with property attributes.
View project → PlanningStatewide heritage overlays joined to every parcel, with renovation and zoning context.
View project → PlanningHistorical zoning fused with planning decisions to predict where rezoning is likely next.
View project → DemographicsPer-microburb dwelling stock, density and growth, with development pipeline overlay.
View project → Market structureWhere investors dominate, where owner-occupiers dominate, and what that does to growth.
View project → RiskAddress-level peril, climate exposure and claim-relevant indices.
View project → PropertyEstimated build year and renovation activity for every Australian dwelling.
View project → InfrastructureUtility and underground asset coverage modelled at parcel level for telcos and distributors.
View project → BehaviourTime-on-market, price drift, withdrawal patterns and agent performance.
View project → PlanningPipeline of approved and pending DAs, joined to demographics and growth forecasts.
View project → LivabilityAffluence, community, convenience, family, hip, lifestyle, safety and tranquillity, scored at mesh block.
View project →Luke Metcalfe, founder of Microburbs and Rapid Intelligence, has been commercialising data since 1998. Selected interviews and appearances below.
Jonathon Moody from Physio Inq describes what it was like to work with Luke from Rapid Intelligence on demand mapping and market modelling.
Booth-level analysis from Microburbs showing the educated and high-income electorates abandoning the Coalition.
Microburbs booth analysis used to explain the realignment of Australian politics by educational attainment.
Microburbs polling-booth modelling cited in post-election analysis.
Booth-level analysis. Working class Labor voters voted No. The educated, rich, godless and childless voted Yes.
Microburbs cited on how to find undervalued properties using livability and noise data.
Microburbs Hip Score used to rank Brisbane neighbourhoods.
Luke walks through how Microburbs combines council minutes, satellite imagery and street view to turn dormant data into investment edge.
Long-form interview on data lineage, methodology and how Microburbs surfaces edge cases the major portals miss.
Luke shares two decades of recruiting and building data teams at Rapid Intelligence and Microburbs.
Luke on the Elephant in the Room property podcast, covering 25 years of validated repeat-sales evidence.
Luke on what actually drives capital growth at street and microburb level.
The Microburbs consulting heritage. Rapid Intelligence was Luke's earlier vehicle, profiling regions down to 160 houses for demographics, psychographics and propensity.
Additional interviews and articles, including the Paul Murray Live political segment, are listed in the consulting prospectus available on request.
Microburbs Consulting is the latest iteration of an Australian data consulting practice that goes back to 1998. The original business, Rapid Intelligence, profiled tiny regions down to about 160 houses for demographics, psychographics and propensity. NationMaster synthesised thousands of country statistics into one comparative engine. NetComber crawled 300 million websites and identified ownership using machine learning, and was sold to a US buyer in 2014.
Microburbs is the property and place-data evolution of that body of work. Same founder, same first principle: build the data layer no one else has, then sell the answers it makes possible. The franchise territory work, political booth analytics, and behavioural CRM for chains all predate Microburbs and remain core capabilities.
Each business solved a different version of the same question: who, where, and what next.
The fastest way to lose a procurement officer's trust is to over-claim. Our edge is predicting human decisions at address level. It is not measuring physical infrastructure or running clinical trials. The line below stays clean on every brief.
Commercialising data since 1998. Founder of Rapid Intelligence, NationMaster and NetComber (sold 2014). Builds the data layer first, then sells the answers it makes possible. Available for direct consulting on briefs where address-level resolution actually moves the answer.
Most consulting briefs we see can be answered in part within a week, because the underlying data is already in our FeatureStore. The first call is free. No pitch, just a working conversation.
