Show clients why these suburbs made the shortlist

A buyers agent can find a plausible group of suburbs in minutes. The harder part comes next: explaining why each one survived the brief, and what changed when the client’s priorities changed.

This example turns one bounded search into a client-ready shortlist. It uses the first four Victorian suburbs returned for houses, all bedroom counts, a Typical Price from $500,000 to $750,000 and High data confidence. These are illustrative candidates, not every match and not the best four suburbs in Australia.

View the demo screenshot

Start with a brief you can show the client

The search holds the basic constraints steady: Victoria, houses, all bedrooms, $500,000-$750,000 Typical Price and High confidence. Typical Price is an adjusted suburb market reference, not a valuation or evidence that every listing sits inside the budget. High confidence is HtAG’s data reliability label based on average monthly sales; it is not certainty about an outcome.

Two saved profiles then express a real client conversation. The Lower Risk emphasis gives Lower Risk RCS a weight of 7 and Cashflow RCS a weight of 3. The Cashflow emphasis reverses those weights to 3 and 7. Saving the profiles makes the choice repeatable: the adviser can show what changed without quietly changing the candidate set.

The figures below are from the reporting period ended 31 August 2026, captured on 17 September 2026. They cover houses across all bedroom counts.

The ranking reveals the trade-off

Higher Lower Risk RCS indicates lower relative risk. Cashflow RCS combines income-oriented indicators such as yield, vacancy and rental trends; it is a score, not a yield percentage.

With the Lower Risk profile, Golden Square ranks first, Ballan second, Ballarat Central third and Bairnsdale fourth. With more weight on Cashflow RCS, Golden Square remains first and Ballarat Central remains third, while Bairnsdale moves from fourth to second and Ballan moves from second to fourth.

The supporting figures explain why that movement deserves a conversation. Bairnsdale has the highest gross yield in this set at 4.84% and a Cashflow RCS of 89, while Ballan has a 3.30% gross yield and a Cashflow RCS of 54. Ballan’s Lower Risk RCS is 79, compared with Bairnsdale’s 67. Golden Square leads both runs, with Lower Risk RCS 81 and Cashflow RCS 95. Those are observations from this four-candidate comparison, not return forecasts.

The returned rank score is separate from the underlying RCS measures. It is the result of ranking these supplied candidates with the selected weights. It is not an RCS, a national percentile or a portable suburb rating. That is why the client should see the candidate set and profile beside the result.

Add context before recommending an inspection

Typical Price, weekly rent and gross yield help a client see the broad price-and-income shape of each area. Gross yield is annualised rent divided by Typical Price before costs and vacancy, so it is not net yield. Years to Own adds area-level affordability context using local incomes, rates and prices under standard mortgage assumptions. It does not describe this client’s loan term, borrowing capacity or likely approval.

The practical next action is a review, not an automatic selection. Confirm whether the priority profile reflects the client, examine current properties and property-level costs, then complete the usual local and parcel due diligence. The ranking helps structure that work; it does not replace it.

A small workload that can be reused

This captured workflow used five distinct operations across six requests: one candidate query, two ranking requests and one request each for summary, scores and fundamentals. Together they returned 24 rows. Operation count, request count and returned rows are different measures; check current HtAG pricing when estimating production use.

A buyers agency could store named profiles, cache a dated candidate snapshot and regenerate the comparison when a new reporting period arrives or the brief changes. Keep the period, filters, candidates and weights with the client note so another adviser can reproduce what the client saw.

Implementation appendix

Check the returned period before joining these responses, because the snapshot requests do not accept a reporting-period input.

Metric definitions follow the HtAG Property Data Dictionary. Start with one common client brief, save two profiles and test whether the comparison produces a clearer shortlist conversation. The HtAG API documentation covers the request details, and pricing helps scope production use.