Machine Learning in Real Estate

Technology has been changing the real estate game for the past decade. Brokerages are becoming more technologically advanced and many have been incorporating helpful tools to help organize and more efficiently manage business. Recently, a popular trend in machine learning has been on the rise.

Essentially, machine learning is a data analyzer. As you provide more and more data to the tool, it becomes more intelligent and learns how to examine said data, organizing it into specific categories. This is a remarkable help in the real estate market, because it helps narrow down clients’ needs, and works in pairing agents with buyers and sellers.

This AI-enhanced tool is a great way to connect with clients, as it shortens the process of understanding what they are expecting in a home. Apps such as Ojo make this possible by offering clients and agents alike with lists of questions to help understand what each of them want. Here’s how it works:

Clients will be prompted to answer questions such as, “What is your budget?” “What neighborhoods are you interested in?” “How many rooms do you need?” “Are you searching for a home based off school districts?” The list goes on.

Agents will be prompted to answer questions such as, “What areas does your brokerage conduct business?” “Are there any homes you are showing at the moment?” “What percentage is your commission?” “How many clients are you willing to take on?” You get the idea.

Based off of these answers, the machine learning technology is able to pair clients with agents who would be able to help them, as well as providing clients with a list of homes that fit their needs. This is great for both clients and agents because it saves an enormous amount of time and gives both parties the important information they need upfront.

Machine learning is on the rise and is something that you may want to seriously consider incorporating into your brokerage – especially before competitors figure it out.