Artificial intelligence like structurely conversational ai has been part of real estate market processes for some time now. Technologies already facilitate various tasks, from the search to the final stages of negotiation, increasingly intelligent and full of resources to help the parties involved.

Although “backward,” the real estate market is already taking advantage of the benefits of artificial intelligence in a concrete way.

Previously outdated in technological terms, the sector began to understand that innovations in the segment can help a lot to ensure better results, and companies started to look for intelligent solutions. Some of them currently mean real revolutions in the market. Check out the primary examples:

Big Data

Big Data is not a unique concept of the real estate market, but companies and their systems very well use it. The massive volume of aggregated information is achieved by AI processes that focus on collecting preferences and particularities of each consumer or other “targets.”

In the case of real estate, we can consider part of Big Data, for example, the neighborhood where a user lives, or if he has been looking for commercial or residential real estate, then offering what will generate more chances of closing the sale.

Simulators

With Big Data and machine learning, it is even possible to make predictions. That’s how real estate valuation and trend simulators work. Through the information obtained, these systems generate numbers with a low margin of error regarding various aspects of the properties.

In the case of real estate trends, numbers from other months are applied to determine the value of m², for example, from some time ahead, all divided by exact locations, such as neighborhoods and even main streets. The same goes for the valuations, which are passed on to those who search based on data already obtained from properties that match the characteristics offered by the user.

Seekers

Search engines, also with the help of Big Data, deliver to the user exactly what he is looking for, increasing the chances of a possible sale. Imagine that you searched for real estate in an X region of the city some time ago. Then he gave up but ended up coming back.

However, this time, structurely conversational ai chose to search for the desired properties by the number of m². The search engine will remember your other attempt and offer you properties that not only meet your size requirements but are also related to the city already searched.