In real estate, there are certain problems that are so old – so firmly entrenched in the process of doing business – they seem commonplace. Imprecise home valuations that affect how a seller prices their largest asset. Unclear or incomplete real estate trends that mislead developers into building properties in inopportune spots. Real estate agents chasing weak leads. Consumers feeling devoid of choice when it comes to practitioners.
But what if all those problems didn’t have to be problems? What if there was a way to harness large sets of data to sweep away some of the opacity and inexactitude gumming up the works in real estate? That’s the thrust behind big data in real estate.
Put simply, big data is the use of massive, diverse and instantaneously accessible data sets. Mining this data for insights has traditionally been too cumbersome for data processing software, but emerging technologies like AI make it possible.
Here’s how big data is changing real estate.
Some real estate thought leaders are using big data to empower customers by offering access to insights and curated choices. Nobul, a real estate digital marketplace, uses an AI-powered algorithm to match consumers with the right real estate agents – based on criteria entered by the consumer. The company analyzes an agent’s sales history, transactions, verified reviews, location, language, etc., to determine their suitability for a given client.
According to founder Regan McGee, “Shopping for the right home is not one-size-fits-all, it is personal, and we aim to facilitate homebuyers’ ability to choose the agent best suited to their needs, and support them end-to-end throughout their real estate journey.”
Big data also helps consumers who want more accurate valuations and appraisals. Because big data combs through large, often unconventional data sets, it can provide a fuller, clearer picture of an asset’s worth in real-time. Consumers can leverage big data to ensure that they list their home for a fair price, or buy a home for a fair price. Accurate valuations also benefit lenders and investors, who have a vested interest in understanding (something approaching) true value.
According to research on big data in valuation from the University of Maastricht, big data AVMs “can provide an instant indication of property value, which saves significant time and resources for portfolios of both investors and lenders, as well as those interested in a single property.”
Developers used to rely on intuition and conventional data (like MLS transaction history) to figure out where to invest millions of dollars. The stakes were high and the insights incomplete – a less-than-ideal way to do business.
Big data helps paint a clearer picture by sifting through non-traditional variables, (average ratings of restaurants in the area, availability of spots at local schools, activeness of street frontage, etc.) and reconciling it with conventional data sets. This ultra-granular, ultra-thorough approach means developers can invest their millions in a surer bet.
Finally, big data also appeals to real estate practitioners who want to effectively market properties, qualify listing leads and analyze buyer behaviours to close deals faster. They can leverage big data to glean insights from various sources – individual public records, user interactions on competitors’ websites, advertising data, etc.
Big data is solving several of the old problems plaguing real estate. And by doing so, it’s making real estate safer, more accurate and more consumer-centric than ever before.