Real estate is a massive industry, and while change has been slow, big data is finally entering the picture and forcing the industry to adapt. Data science and artificial intelligence have made significant inroads into the real estate industry, innovating and disrupting traditional business practices.
Models have been developed that use public data to analyze information to determine neighborhood quality and price per square meter.
Property Search Software
The evolution of property matching software has been a big revelation in data science in real estate. In other words, AI bots sift through a plethora of property listings to identify the best matches.
Property matching software can offer more options and parameters than real estate agents on their own. However, when used by an agent, they provide clients with more precise information and better matches in less time.
Models of Value
Data science is being used for more than just matching clients with the perfect property. Other applications also include accurate estimates of a house’s price (which, depending on the market, may differ significantly from the appraisal) or even attempts to time the best time to buy an investment property.
Valuation models aim to create a better estimate of the property in question by using data from previous transactions. It is a technology already being used by several real estate platforms.
Analysis of Clusters
The real estate industry is far from uniform. Performance varies greatly depending on location and subsectors. Luxury villas and mass-market condos operate in very different environments. Real estate trend lines can vary significantly between cities and even neighborhoods.
The goal of cluster analysis is to identify such patterns and determine which subsets of properties will perform similarly.
Are Real Estate Agents Concerned?
Some real estate agents are concerned that big data and AI bots will become obsolete. At least one innovative real estate Tech Company does not believe that will happen, but it does believe data science will significantly disrupt the industry.
Nobul is the world’s first open digital marketplace in which real estate agents compete for the attention of home buyers and sellers. It is a consumer marketplace similar to Uber, but it also provides real estate agents with tools such as AI technology and blockchain to help them do their jobs more efficiently.
Regan McGee, Nobul’s founder and CEO founded Nobul to shake up the industry and create a more consumer-centric option. “We are building a full eco-system, edge real estate, consumer-centric,” McGee told BNN Bloomberg. Buyers or sellers never pay us. They have never seen an advertisement. The entire process of buying and selling real estate is competitive. Real estate transaction costs account for 1.9 percent of our GDP. That is not property value; it is transaction value.
Data science has significantly altered the real estate agent’s role, and as platforms like Nobul grow in popularity, more and more agents will be forced to adapt. Still, buyers will always want someone to assist them individually with such a significant transaction.
Where Does Information Come From?
Because real estate is such a massive industry, a wealth of data is available that intersects with various economic and social factors. Data is gathered from available data sets, transactional data, and even information directly related to a building.
Data science will play an increasingly important role in real estate. Agents who ignore data science risk losing a lot of business as rivals use intelligent data analysis to assist their clients in making better decisions.
