Listings churn weekly. Neighbourhood, school-catchment, commute and price-trend pages do not — and they are what people search before they search a property.
Neighbourhood and trend layers outlive listings.
Sold, withdrawn and expired all handled.
Registry, census, transport and school data.
Price and days-on-market recalculated.
Modelled at current defaults: 384 indexed URLs → 152 valuation enquirys per month.
Property SEO fails when the whole strategy is listing pages: they expire, they duplicate across portals, and they carry supplier photography and copy. The durable layer sits above listings — neighbourhood guides, price trends, commute analysis, catchment areas, building profiles — generated from data that updates rather than expires. Listings then become the internal-link payoff at the bottom of those pages.
Listing URLs 404 or thin out the moment a property sells.
Every portal publishes the same feed, so nothing differentiates.
Neighbourhood pages are three paragraphs of generic prose with no data.
Neighbourhood, catchment, commute and price-trend pages generated from public and licensed datasets that refresh instead of expiring.
Sold, withdrawn and expired listings routed by rule — retained with sold-price data, redirected to the neighbourhood, or deindexed — never left as an empty shell.
Price-per-square-metre trends, days-on-market history, transport times and school data, presented as the analysis a portal feed cannot produce.
Place, RealEstateListing and Organization schema, plus location-page architecture that does not create thousands of near-identical suburb pages.
Listing feed, historical transaction records, census demographics, transport timetables and school performance data joined onto a common geography.
Joined geographic dataset by area.
These are patterns, not a keyword list. Each one multiplies against the entities in your own dataset — which is where a 620-URL first batch comes from.
Not yet. Fix the unchecked items first; publishing now would create pages we would later consolidate.
Brokerage and portal builds where conversion is a valuation or viewing request. Indexation is held at a conservative 62%.
A model, not a forecast. Move the sliders to your own conversion economics — we will run the same maths against your data on the call.
| Dimension | The usual approach | With WpBulkPublishing |
|---|---|---|
| Primary asset | Listing URLs | Area and trend pages that refresh |
| Differentiation | Shared portal feed | Registry, census and transport analysis |
| Expiry | 404 or thin shell | Rule-based retain, redirect or deindex |
| Geography | Every boundary gets a page | Only units with search demand |
We look at what real estate marketers already hold — systems, exports, APIs — and score each axis for demand and defensibility.
The data contract is written and the first template is designed against real rows, not placeholders.
93–217 URLs published with schema, internal links, sitemap entries and IndexNow.
Indexation and impression data decides what widens and what gets cut. Templates, gates and runbook transfer to you.
The durable layer mostly uses public data. Feed data is used for the live rails, which is normally within licence terms — we check yours before the build.
Each role gets its own data reality, its own template families and its own definition of a good outcome. Pick the seat you sit in.
We audit your data, size the first batch, model the economics and tell you honestly when programmatic is the wrong tool for the job.