Listing Evaluator
Paste a PropertyGuru or 99.co listing URL to compare against our market data.
Evaluate a Listing
Paste a PropertyGuru or 99.co listing URL to compare against our market data.
How to Use the Property Evaluator
Reviewed by ShiokNest Editorial Team Updated Data sources Methodology
Key Takeaways
- This advisor asks a few short questions and returns a personalised recommendation.
- All calculations run in your browser — no data is stored or sent to a third party.
- Re-run the advisor with different inputs to compare scenarios side-by-side.
What It Does
The Listing Evaluator takes a specific property listing — from PropertyGuru or 99.co — and benchmarks the asking price against actual URA transaction data for the same development. You paste the listing URL (or manually select a development name from the dropdown), choose whether it is a sale or rental listing, and enter the asking price, unit area in square feet, number of bedrooms, and floor level. The evaluator matches your inputs to the corresponding development in ShiokNest's database and computes the asking PSF versus the development's median transacted PSF, median rental for the same bedroom type, estimated gross yield at the asking price, and floor-level premium versus the development's ground-floor baseline.
The output is a verdict card: "Below market," "At market," or "Above market" — accompanied by the percentage gap between asking PSF and the 12-month median transacted PSF for comparable units in the same development. For rental listings, it computes the asking rent versus median rent for the same bedroom count, and flags the gross yield the landlord is implying at that asking price versus what the development has historically achieved. You can find the Listing Evaluator on ShiokNest under the Advisor tab — it runs entirely in your browser with no data stored. Results are instant once a development match is confirmed.
Why It Matters
Singapore property listings carry asking prices that can vary 10–25% above actual transacted values — and there is no standardised mechanism forcing agents to justify asking prices with data. A seller or landlord who paid peak-2022 prices or is anchoring to a neighbour's aspirational listing can set any asking price, and without transaction data, buyers and tenants have no objective reference point. The Listing Evaluator solves this: it retrieves the actual prices that units in the same building cleared at over the past 12 months and tells you — in seconds — whether the asking price is within the market range or significantly above it. This information alone can save a buyer $50,000–$150,000 in negotiation.
The most important number the evaluator returns is the PSF gap — the percentage difference between the asking PSF and the 12-month median transacted PSF for comparable units in the development. A gap of +5% is normal (sellers ask above median and negotiate down). A gap of +15–20% means the seller is pricing significantly above what the market has actually cleared, either in expectation of finding a less-informed buyer or because they are anchoring to an outdated or outlier transaction. Knowing this gap before you make an offer tells you the realistic negotiation floor, and whether it is worth negotiating at all or walking away.
For rental listings, the evaluator is equally powerful. Singapore rental asking prices are highly variable by landlord — some price at market, others ask 20–30% above what similar units rent for in the same building, relying on tenants who do not know the going rate. The gross yield that a landlord is implying at their asking rental versus what the building has historically yielded is a direct signal of whether the rent is fair. A landlord asking $5,200/month for a 2-bedroom in a building where the median rent for 2-bedrooms is $4,200 is asking for a 24% premium over market — something that is obvious in the evaluator's output but invisible to a tenant who only sees the listing and not the transaction history.
The floor-level premium component is particularly useful for evaluating units priced at a high-floor premium. A seller who claims their floor-28 unit commands a 20% PSF premium over similar low-floor units can be verified against what the floor-premium data actually shows for that development. In many cases, sellers overestimate the premium their specific floor commands relative to what the market has paid. Use the Listing Evaluator before every viewing — it takes 30 seconds and gives you a data-backed position before you enter any price negotiation. Pair it with the Floor Premium Insight for the district-level floor curve, and the Mortgage Calculator for total financing cost at the asking price.
How It Works
- Answer each question honestly — the recommendation is only as good as the inputs.
- Review the weighted score breakdown to understand why each option ranks where it does.
- Click through to the linked calculators or insights to dig deeper on any single factor.
- Re-run with different inputs to see how sensitive the recommendation is to each answer.
Tips & Pitfalls
Expert Tips
- Run the advisor twice — once with best-case assumptions, once with worst-case — to see the full range of outcomes.
- Pair the recommendation with the relevant calculator below for the dollar-level detail.
- Share the result with your spouse or financial planner before acting on a large commitment.
Common Pitfalls
- Treating the score as a prediction — it is a decision framework, not a forecast.
- Ignoring factors outside the model — school catchment, family plans, and lifestyle fit are not scored here.
- Over-weighting a single input — change one answer and see how much the score moves before trusting it.