Methodology

How the opportunity score works

Every subzone on the SiteMetriq SG map has an opportunity score from 20 to 90. This page explains what goes into that score, where the data comes from, and what the score is, and is not, designed to tell you.

332

Subzones scored

52,894

URA rental transactions

113,394

Zoning parcels mapped

13,021

Development records

Built using

URA rental transactions
LTA MRT ridership
SingStat demographics
HDB dwelling data
URA development pipeline
URA Master Plan zoning

Each dataset refreshed on its own official publication schedule

Score scale

78 to 90High-potential area
68 to 77Strong area
55 to 67Moderate area
40 to 54Challenging area
20 to 39Weak area

The map describes areas. Decision guidance for a specific address, concept, and quoted rent is produced separately in the address report, with its own verdict scale.

Why trust the score

The free map score is built entirely from Singapore government datasets, not proprietary or scraped data
Every subzone scored using the same consistent methodology
Confidence measures reduce the influence of lower-resolution inputs
Known limitations documented openly on this page
Designed for comparing opportunities, not predicting business success

Our philosophy

Most location tools answer: where are the busiest places?

SiteMetriq answers: where does an independent business have the best chance of succeeding?

These are different questions with different answers. A location can be extremely busy and still be a poor opportunity for an independent operator, because rent is too high, competition is too entrenched, or the foot traffic does not match the business concept.

The opportunity score is comparative, not absolute. A score of 75 indicates a stronger opportunity relative to other Singapore subzones, not a guarantee of commercial success. Read it alongside the area characteristics and evidence behind it, not as a standalone probability.

The address report layer

Government datasets tell SiteMetriq about an area. The paid address report adds a second layer: the specific businesses operating at and around a given address at the time the report is generated, plus higher-resolution government data that only becomes meaningful at address level.

None of this layer is part of the free map score, which is based entirely on the government data described above. In the address report it provides:

Named competitors within the search radius, classified by category and threat level
Anchor tenants that drive foot traffic (supermarkets, MRT exits, offices, schools, hawker centres, mosques)
Nearby amenities relevant to the specific business concept
Competition density and dominant player identification
Updated at report generation time, not pre-cached

The report also draws on additional government datasets at address-level resolution:

LTA Bus Passenger Volume

Bus stop tap-out volumes within walking radius of the analysed address

Monthly

HDB Resale Transactions

Resale price per square metre, rolling 12-month median, as a current wealth signal

Monthly

MOE School Directory and NEA Hawker Centres

Authoritative locations of demand anchors near the address

Periodic

URA Master Plan parcel zoning

Whether commercial use appears permitted at the exact address

Plan amendments

The address report combines a live business-data layer with the government datasets described on this page. Neither layer alone is sufficient. The combination is what makes an address-level report meaningfully different from the area-level map.

Why a map search is not enough

Map search tools are excellent at showing what exists nearby. They are not designed to answer whether a location is a good commercial opportunity, because that question depends on more than visibility.

High foot traffic does not equal a good business outcome. Much of that traffic may be commuters passing through, not customers.
Cheap rent alone does not equal a good business outcome. Low rent in a low-demand area can still fail.
Population density alone does not equal a good business outcome. Residential density matters less if local income or competition makes the concept unviable.

SiteMetriq combines demand, affordability, accessibility, and commercial saturation into a single score, because no single metric reliably predicts opportunity on its own.

Why Orchard Road does not score highest

Orchard Road and Raffles Place generate enormous economic activity. They score in the moderate range because they also carry the highest commercial rents in Singapore and the most intense competition from established operators and international chains.

A location with lower operating costs and sufficient demand can represent a much stronger opportunity than the busiest district. That is exactly what the score is designed to capture.

SiteMetriq measures opportunity for independent operators, not absolute economic activity. A score of 45 in Raffles Place does not mean the area is economically weak. It means the conditions for a first-time independent operator are genuinely difficult there.

How the score is built

Each signal is normalised before being combined, so no single raw metric dominates purely because of its scale. The flow from raw government data to a final score:

Government data (URA, LTA, SingStat, HDB)
Normalise each signal to a common scale
Demand · Affordability · Transit · Saturation · Pipeline
Business type adjustments
Opportunity score (20 to 90)

Score components

The score combines five signals. Their relative influence varies by business type. A clinic weights residential density differently than an F&B operator weights transit access.

Demand

Composite of resident population, daytime population, household income, and MRT ridership. In commercial cluster zones, MRT tap-out volume is used to estimate worker population where Census data understates the true workforce.

Affordability

Based on URA median commercial rent PSF for the planning area. Lower PSF relative to the Singapore median increases the opportunity score. Benchmarks updated as URA releases new quarterly transaction data.

Commercial saturation

A penalty applied to areas with established commercial saturation. High-saturation planning areas including Downtown Core and Orchard receive a saturation penalty that reflects genuine barriers to entry for independent operators.

Transit access

MRT effective volume calculated as station tap-out with exponential distance decay. Stations within the subzone receive near full weight. Distance beyond 800m receives significantly reduced weight, reflecting observed walking behaviour.

Development pipeline

Approved URA residential and commercial pipeline within a 24-month window. A positive pipeline signal adds a small growth bonus. This signal is intentionally minor: the score reflects current conditions, not projected ones.

Data sources

All map-layer data comes from Singapore government agencies. No proprietary commercial datasets are used in the free map scoring model. Each source is refreshed on its own official publication schedule.

URA

Quarterly

Urban Redevelopment Authority

Commercial rental transactions and lease records across all 55 planning areas. Used to derive median rent PSF benchmarks by district.

Coverage: 55 planning areas

LTA

Monthly

Land Transport Authority

MRT and LRT station level tap-in and tap-out ridership by hour and day of week.

Coverage: 182 stations with ridership data

SingStat

Census 2020

Singapore Department of Statistics

Resident and daytime population by subzone and planning area. Median household income by planning area.

Coverage: 332 subzones, 55 planning areas

HDB

Annual (2025)

Housing and Development Board

Dwelling unit counts and block-level data by planning area. Used as a proxy for residential demand density.

Coverage: 13,289 blocks

URA MP

Monthly (pipeline)

URA Master Plan and Development Pipeline

Land use zoning at parcel level, development status, planning area boundaries, and approved pipeline projects.

Coverage: 113,394 zoning parcels, 13,021 pipeline records

SLA / Google

Current

OneMap (Singapore Land Authority) and Google Geocoding

Address resolution. OneMap is used to assign planning area and subzone during dataset ingestion. Address reports use Google Geocoding as primary with OneMap as fallback.

Coverage: All Singapore addresses

URA publishes commercial rental transactions at planning area granularity, not by subzone. SiteMetriq uses the highest resolution public benchmark available for rent and applies confidence weighting wherever subzone precision is not possible.

Restricted and non-commercial zones

Not every subzone is commercially viable. Military installations, offshore industrial islands, nature reserves, and undeveloped future zones are flagged separately and appear greyed on the map.

SiteMetriq distinguishes between hard restricted zones where commercial activity is not permitted, and penalised zones where commercial activity is difficult but possible. Future development zones such as Tengah new town are penalised but not excluded. They represent genuine long-term opportunities that will be rescored as development progresses.

CategoryExamplesTreatment
MilitarySafti, Murai, Lim Chu Kang, Pioneer SectorScore cap 15
Offshore industrialJurong Island, Bukom, SemakauScore cap 15
Airport and portChangi Airport, Changi Bay, Brani TerminalScore cap 20
Nature reserveCentral Water Catchment, Coney IslandScore cap 25
Heavy industrial B2Tuas North, Tuas Bay, Joo KoonScore penalty
Future developmentTengah, Marina East, Woodlands Regional CentreScore penalty, not greyed

Known limitations

Being transparent about what the score cannot do is as important as explaining what it can.

Subzone-level granularity

The score represents the subzone average, not a specific unit. Two units 50m apart in the same subzone can have very different commercial viability. Address-level analysis in the paid report accounts for this.

Census daytime population

The Census measures resident population by subzone of residence, not workplace. Commercial cluster zones have very low Census daytime figures despite large worker populations. SiteMetriq uses MRT ridership as a proxy in these zones, but this is an estimate, not a direct count.

Rent benchmarks are planning-area level

URA rental data is aggregated at the planning area level. Rent PSF for Tampines represents the average across the entire planning area. Actual rent for a specific unit may vary significantly.

Competition is not directly measured on the free map

The free map uses a saturation signal reflecting broader area patterns, not individual competitor counts. Live competitor analysis is generated per address at report time.

Business type weights are approximations

The differences in relative influence between business types are based on general commercial principles, not empirical studies of Singapore business survival rates by location. Treat type-specific scores as directional, not precise.

Update schedule

Each data source is refreshed on its own official publication schedule. The scoring model re-runs when new data becomes available.

LTA MRT ridershipMonthly
LTA bus passenger volume (report layer)Monthly
URA development pipelineMonthly
HDB resale transactions (report layer)Monthly
URA commercial rental PSFQuarterly
HDB dwelling unitsAnnual
SingStat population and incomeCensus 2020 (decennial)
Land use zoningURA Master Plan amendments

Calibration and accuracy

The scoring model has been iteratively calibrated against Singapore's public datasets and observed commercial characteristics across benchmark districts. The underlying signals, rent, transit, demand, and saturation, are grounded in the government sources listed above rather than in subjective judgement.

Where the score surprises people, we investigate. Sometimes the model is right and intuition is wrong: Orchard scoring in the moderate range is the canonical example, and the reasoning is documented above. Sometimes a known data limitation is the cause, such as Census daytime population understating worker density in commercial clusters, and those cases are listed openly in Known Limitations.

The current version reflects the best available calibration against Singapore public data as of 2026. Opportunity scores are designed to support screening and comparison, not to replace due diligence on a specific commercial unit.

Why the map is free

The public map is designed to help business owners narrow down promising areas before investing time visiting properties. Exploring 332 subzones visually takes minutes. Visiting ten properties takes weeks.

Once you have shortlisted a location, the address-level report provides substantially more detail: live competitor analysis, exact commercial rent benchmarks, rent feasibility modelling, and unit-specific insights that cannot be shown at subzone level.

Important disclaimer

The SiteMetriq opportunity score is an analytical tool based on publicly available government data. It is designed to support, not replace, informed decision making. A high score does not guarantee business success. A low score does not mean a location is unviable for every business concept.

Business success depends on factors that SiteMetriq does not and cannot measure: management quality, product quality, marketing, capital adequacy, lease terms, and market timing. SiteMetriq should be used as one input among many, alongside physical site visits, conversations with existing tenants, and professional advice.

SiteMetriq is not a licensed financial adviser, property consultant, or business adviser. Nothing on this platform constitutes professional advice. Always seek qualified professional advice before making significant commercial commitments.

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