What a report measures, and how.

About Site Intelligence

Site Intelligence is a Singapore location-screening product: it turns the question “should I open an outlet here?” into an explainable, benchmarked scorecard for a specific address. Reports are built from government and licensed data, an explainable scoring engine, and automated commentary that is never presented as human analysis.

Signal categories

A report scores a site against roughly 18 signal categories. Each is benchmarked against published Singapore data and shown in the report with its weight and contribution — nothing is hidden behind a composite.

• Population and demandResident population and density in the trade area; age structure (children, working-age, elderly); household composition.
• Affluence and spending powerHousehold income by planning area; HDB resale prices as corroboration; dwelling-type mix (HDB / condo / landed).
• Accessibility and transportBus-stop density; nearest rail station and its ridership; walking reach and walk-time bands; carpark supply.
• Land use and zoningThe site's zoning and the surrounding land-use mix — retail, residential, office and commercial potential.
• CompetitionCount of comparable businesses nearby from Google Places, where a clean category exists. Marked 'not assessed' for verticals with no clean type.
• Institutional proximityNearby schools, universities, childcare centres, hospitals, malls, parks and hotels — curated, licensed lists.
• Context and characterPlanning-area character and commercial context that shape how a site is used day to day.

Data sources

• Singapore Department of Statistics — Census of Population 2020 (population, income, dwelling and household data)
• Urban Redevelopment Authority — Master Plan 2019 land-use zones and plot ratios; subzone boundaries; MRT and LRT station locations
• Housing & Development Board — resale transactions
• Land Transport Authority — bus-stop locations and rail ridership
• OneMap (Singapore Land Authority) — geocoding and basemap tiles
• Curated, licensed institutional lists — schools, childcare, hospitals, malls, parks and hotels (compiled and maintained by us)
• Google Places — live competition counts and named nearby businesses (a paid, per-report call)

How scoring works

Each address is scored against roughly 18 signal categories. Every signal is measured against Singapore benchmarks (percentiles among published subzones or planning areas) and given a weighted contribution toward the concept-fit score. Weights come from the chosen business vertical's profile — a budget gym and a premium café weight the same signals differently. The result is an explainable score: you can see which signals helped, which dragged, and why.

Percentiles are always shown with their comparison population — a population score means "among all published Singapore subzones"; an affluence score means "among published planning areas." A suppressed figure is shown as unavailable, never guessed.

Walking catchments and trade areas

Reports show three straight-line rings around the site (primary, secondary and fringe bands) with the residents, transit, carparks and land use in each. Where a walking-network isochrone is computed, it is shown as a separate, clearly-labelled view: modelled network reach within walk-time bands, with the explicit caveat that actual entrance routes, crossings and indoor mall circulation are unverified.

Competition

Competition is a live count of comparable businesses near the site from Google Places, where a clean category exists for the vertical. Two things to know:

• For verticals with no clean Google Places type, competition is marked not assessed rather than shown as a zero — the report is explicit when it is not measuring something.
• Named nearby businesses shown in the hosted view expire 30 days after generation and are then removed, per our data-use terms.

Data freshness and vintages

Sources carry their official vintage: Census of Population 2020, URA Master Plan 2019, and the most recent available LTA and HDB datasets. Competition counts are live at generation time. Where a dataset's refresh date is not tracked, the report says so rather than inventing one.

Every report also carries its own generation date and a data-coverage indicator (high / partial / low) — so a reader can see how current the figures are and how much of the full signal set was computable for that site.

Version

This methodology corresponds to Methodology version 1.0 — the same version number shown in every report's footer.

Measured versus modelled versus inferred

Measured: sourced facts from government or licensed datasets (population, transit stops, land-use zones, resale transactions). Modelled: values derived from those facts (area-weighted resident estimates per ring, density benchmarks, walk-network reach). Inferred: interpretive statements — always labelled as such (for example "this suggests…" or "a hypothesis worth verifying on site"). Footfall, customer behaviour and sales are never measured here, and the report never claims they are.

Automated commentary

Limitations

Built for early-stage site screening. It does not replace a site visit, lease review, financial model or professional advice.

This product is designed for early-stage screening and shortlisting. It does not provide primary market research, rent valuation, structural or lease review, or on-the-ground verification — those remain the work of a site visit and professional advice.