Selling and buying a house with Artificial Intelligence

AI-powered tools are also about to become central in real estate companies to help agents close deals faster. While selling and buying homes remain a relationship business and therefore consistently in the hands of real estate agents, IT can play a significant role in simplifying and automating the processes in which humans have traditionally been involved. At the center is all the activity related to cloud computing and data analysis, as well as algorithm improvements. Realogy uses more than 25 artificial intelligence models, including models that can help agents predict their chances of recognizing customer potential and others that can predict the optimal percentage split between a broker and agent on a property. Compass instead implemented an AI-powered tool that predicts whether people in an agent’s contact database will sell their homes within a year. In the second half of 2020, the indications of these models led to 94% exact results. Agents can thus move in advance and contact the identified people directly by proposing to sell. Certainly a more comfortable and less empirical tool than knocking on doors or relying on word of mouth as is the tradition of the trade. The model takes into account a number of variables to make a prediction, including how often homes are sold in that region, the last sale price of each property, and how much the home has increased in value over time. Zillow recently unveiled Zestimate, a tool that estimates the market value of a home powered by a self-learning neural network and takes into account hundreds of millions of parameters. Ranging from the square footage of the house and its location to the differences from the surrounding houses. Although AI networks cannot yet explain the human intuition or empathy behind buying and selling a home as a deeply emotional and risky factor. It is difficult to think that human contact can be circumvented but, in any case, technology can add value both in the research phase for buyers and in the management of the rational components that make up the work of real estate agents.

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