A practical workflow for real estate agents and property managers

Prepare a rental appraisal evidence pack from recent listings

A rental appraisal often begins with several browser tabs, a subject property in the CRM and nearby listings that do not use the same comparison criteria. The evidence may be useful, but turning it into a consistent client-ready pack takes time.

A property-data workflow can prepare that first evidence set automatically. It can match the subject address, retrieve its physical attributes, apply the same property, bedroom and bathroom criteria to recent nearby rental listings, and place every selected comparable on a dated map and table.

The result is a reviewable starting point for the agent or property manager. It shows advertised weekly rent evidence, not achieved rent. The professional still completes the appraisal using inspection knowledge, condition, improvements, presentation and inclusions.

Start with a matched and complete subject property

The workflow begins with 226 Railway Parade, Noble Park VIC 3174. Address geocode matches the entered address to canonical key 226RAILWAYPARADENOBLEPARKVIC3174 and provides the coordinates used for the evidence map.

The HtAG property summary records a house with three bedrooms, one bathroom, two car spaces and 606.81 m² of land. The property attributes were refreshed 29 August 2026. The most recent recorded rental advertisement in property history was $550 per week on 17 September 2026, with the same three-bedroom, one-bathroom and two-car-space identity.

That historical amount is an advertised rent. It does not establish the rent agreed in a tenancy.

Apply one comparable brief to the whole search

The fixed snapshot uses a 2 km radius with proximity=any, houses, exactly three bedrooms and one bathroom, advertised-rent values required, and listing dates from 1 April to 30 September 2026. The request returns ten rows on this page. The subject is removed by exact address key, leaving nine comparable listings.

Every published comparable has a matched address, advertised weekly rent, listing date, property type, bedrooms, bathrooms, car spaces, distance from the subject and coordinates. The sample was chosen for record completeness; the rents were not used to choose which valid rows to retain.

Keep observation, interpretation and action separate

Observation: the nine comparable listings have a median advertised rent of $577 per week. Half sit between $565 and $610 per week. The most recent comparable is 8 Devonshire Drive, advertised on 25 September 2026 at $650 per week. The nearest is 5 Jonathan Court, 0.729 km from the subject, advertised at $590 per week on 23 September 2026.

Interpretation: the selected recent listings provide a consistent local advertised-rent reference for properties matching the subject’s type, bedroom count and bathroom count. The interquartile range makes the centre and spread visible without allowing one listing to define the conversation.

Suggested action: review the comparable table and map, then add inspection knowledge about the subject’s condition, improvements, presentation and inclusions. Record which comparables remain persuasive and use the completed evidence pack in the landlord discussion.

This keeps API-supported evidence and professional judgement distinct. The output is an evidence pack for a human-reviewed rental appraisal, not an automated rent determination.

Reuse the workflow without rebuilding the evidence manually

The workflow uses four distinct HtAG operations across 13 requests and returns 31 rows. Ten requests are address matches: one for the subject and nine for selected comparable coordinates. Distinct operations, requests, returned rows and billing are separate measures.

Cache the accepted subject address key and the reviewed fixed snapshot under the agency’s retention policy. Keep the search window, radius, property criteria, subject-exclusion rule and quartile method with the evidence pack so another team member can reproduce it. The interactive comparison makes no reader-time HtAG request. The captured map uses an OpenStreetMap basemap with visible attribution.

Implementation appendix

The HtAG API documentation covers the four operations used:

1. GET /address/geocode — match the subject and bounded comparable addresses to canonical identity and coordinates.
2. GET /property/summary — retrieve the subject’s physical attributes.
3. GET /property/rented/search — retrieve recent nearby rental listings with explicit date, radius, property-type, bedroom and bathroom filters and includeRentValueUnknown=false.
4. GET /property/history — retrieve the subject’s rental-advertising history using sold=false and rented=true.