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Big data and AI is the go-to to interact with potential real estate clients

  • Gina 

Real estate is poppin. It’s a sellers’ market, and real estate brokers, agents, and investors are working overtime to make deals happen. The pandemic has turned traditional marketing tactics upside down since many in the field would host face-to-face meetings, events, and showings. 

Because of this market shift in how homes are now found and shown, some of the most successful brokerages have deeply invested in tech for their firms and to connect with potential buyers and sellers. You are probably already familiar with many of these marketing-related tools like software for 3D virtual tours and for hosting virtual open houses and showings. But behind the scenes, virtual operations, artificial intelligence, machine learning and data analysis are driving the real estate industry. 

One emerging area we see developing is the use of big data for more accurate property valuations. My neighborhood is a hot area for buyers, and it was only on the market for less than 24 hours when I saw it. (From list to accepting my offer was approximately 36 hours.) It was priced fairly, accurately, and the listing agent compared market trends to make my listing HOT. This type of data is important both for sellers to price their properties accurately, and for buyers to know when to make a full-price offer and when a lower offer might be appropriate, especially when time may be of the essence.

Another trend is providing deep insights into specific properties. A detailed and complex list of previous insurance claims and permits, neighborhood details including home values, crime rates, school districts and performance levels, demographics and proximity to fire stations, emergency rooms, and sinkholes are a must to know. 

There is also a developing trend in predicting consumer behavior to get listings before the homeowner even realizes they’re ready to make a change. According to RISMedia “Data analysis is more than reactive; it can also be predictive. Tracking mortgage payments and home equity, and matching that information with the age of a home and how long the owner has lived there, can help agents recognize when someone might be getting ready to sell. Data can be used to analyze potential leads and increase the probability of higher quality leads.”

The last trend: model building performance for investors. When I purchased my home, I knew this was going to be a place I lived for 3-5 years and then rent it out for the next 10+ years and then sell it – it’d be a safety net, go towards the retirement fund or a college fund for possible future child(ren). I did research on rental rates, vacancy rates, and bigger trend information. I paid attention to the cars in the driveways and the maintenance of the grounds to determine that this property was the best fit I was looking for. This was a very manual process – especially for investors with multiple homes, analyzing and tracking the market data and predicting trends is better done with intelligent software. 

A commonality for these four trends are the fact that many in the real estate space have seen dramatic shifts in the way they market, keep investors and potential clients engaged and informed, and have built big data new methods of analysis to simplify the process and focus on the bigger picture: building healthy and long term relationships with their clients.