Machine Learning is a field of computer science where computers learn from data without being explicitly programmed to do so. It’s one of the most effective ways to power artificial intelligence and its real estate applications are endless. Three of the applications we’re most excited about are:

  1. Improving CMAs – determining property valuations can be challenging as there are so many factors that influence price. Current appraisal techniques are often based on a previous sale price, failing to take into account factors like transportation and infrastructure improvements, changes in the environment, local neighborhood, and other amenities (like schools, stores and access to public transportation) that have an impact on a property value. Due to pattern recognition abilities, Machine Learning software can greatly increase the number of price-affecting factors analyzed and significantly increase accuracy. Instead of current valuation techniques like using previous sales data and similar homes currently on the market, Machine Learning could process exponentially more data points that have an impact on property values – factors like transportation and infrastructure improvements that change commute times and walkability, changes in the environment, local neighborhoods, schools, points of interest, and more. Moving beyond the valuation itself, Machine Learning software can also streamline the negotiation process by predicting the price the property will actually sell at and setting much more accurate benchmarks for offers, easing the tension brokers face every day.
  2. Personalized Marketing Automation – machine learning can power large recommendation engines that will know the best time to contact a potential or past buyer and seller, the buyer or seller’s criteria (do they need a fast sale or the maximum dollar amount, for example; for buyers, what neighborhood and property is best for their lifestyle), their preferred communication method and more.

  3. Operational Efficiencies – while some fear automation, AI and Machine Learning will render real estate agents obsolete, we believe the efficiencies created through Machine Learning will actually make agents who embrace technology significantly better at their jobs and more relevant to the consumer. From scoring leads and listings to improve Marketing Operations to learning from buyer and seller data gathered throughout the sales cycle to improve Sales Operations and agent productivity, the operational applications of Machine Learning are just as powerful, if not more, than the consumer-facing applications.

There are companies already using Machine Learning for real estate today, like Skyline AI who says “its technology is trained on what it claims is the most comprehensive data set in the industry, drawing from more than 100 sources, with market information covering the last 50 years. Its technology is meant to provide faster and more accurate analysis than traditional methods, so investors can react more quickly to changes in the real estate market.” At Union Street Media, we’ve applied Machine Learning to help us match property criteria and standardize data across MLSs. One thing that’s certain is while other industries have already benefited from Machine Learning driven technology for years, the emerging applications for real estate are poised to accelerate growth and innovation for companies who embrace the possibilities of it.