How to prepare a property listing people and AI can understand

Start with the buyer’s decision

Imagine someone looking for a two-room apartment for sale in a particular city, within a budget and with parking. They need to establish whether your offer fits. An AI application needs the same clear facts. A price hidden in an image, contradictory room counts and implied parking arrangements create uncertainty that polished copy cannot resolve.

Here, an AI-ready listing means one whose facts can be checked and passed consistently to another system. It is a data-quality goal, not a promise that an assistant will select or recommend the property. Begin with one actual listing before applying the structure across your inventory.

Give each property a clear identity and location

Assign a stable internal identifier and an individual source link to each property. A development name is not an apartment identifier: one building can contain several similar units. Keep the identifier when the price, photographs or headline change. This lets you distinguish an update from a genuinely new property later.

Use a descriptive title and separate fields for the important attributes. If you cannot publish the full address, choose a consistent permitted level of location detail and explain it. Do not invent precise coordinates from a neighbourhood name. A precise-looking guess can mislead more than an explicitly unknown value.

• The property ID and source link survive ordinary editorial changes.
• Country, city and published address agree.
• Development, building and individual property names are distinguishable.

Make numbers comparable

Provide price together with currency and transaction type. For rent, explain the rental period and distinguish additional charges from the principal amount. Do not use zero for an unknown price. State the area unit and distinguish total, living and land areas when more than one applies. Do not silently substitute bedroom count for room count.

An illustrative record might read: “Apartment A-204, 54.2 m², two rooms, for sale, EUR 189,000; parking offered separately.” This lets a reader compare the core offer and recognise an exclusion. If the parking price is unconfirmed, leave it unconfirmed rather than inventing an amount or adding it to the total.

Keep descriptions and photographs consistent

Choose photographs of the actual property and label visualisations clearly. A shared courtyard should not appear to be a private terrace. Describe what the image really shows and check that its public link works without signing in. A company logo is useful branding, but it does not replace a property photograph.

Structured markup describes information; it cannot replace the visible listing. Schema.org distinguishes a listing from a dwelling type such as Apartment. Google’s guidelines require structured data to reflect the page content. Reconcile the facts before validating the markup: technical validity does not establish that an assertion is true.

Run a final review before distribution

Ask a colleague who has not seen the property to explain what is offered, what it costs and what remains uncertain. Record specific gaps instead of a general “looks good”. After importing into FindEstate, review missing fields, manual corrections and hidden records in the workspace. Receiving records is a separate step from publishing a catalog.

Check availability and the latest source observation separately. Rights verification, catalog review and permission to distribute are distinct decisions. A fully populated listing should not be presented as available when it is reserved or sold. Repeat the review after a significant source or import-format change, and assign someone to resolve each discrepancy before it becomes a repeated customer question.