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Agents could use big data on a national scale to identify and predict buyer and vendor preferences in the future and provide customised services, according to an executive.
Propic chief executive Jeff Gray noted that valuable data is currently sitting in property management and CRM systems in real estate, but these systems are not designed to utilise big data on scale.
However, he added that extracting that data out of core systems on a national scale would enable agencies to answer questions such as which properties, buyers, and vendors are more likely to transact in the future.
“To find a real practical use case for big data, we need to ask ourselves how we could take a reactionary business or a process like prospecting for new listings, and use data on a national scale that enables you to identify and predict what consumers are going to do in the future,” Mr Gray told REB.
“Companies like Propic and CoreLogic have automated valuation models for predicting property prices but I think the real opportunity lies not so much around property pricing but rather how we could connect buyers and vendors with the services they need in real estate, and how we could do it in a proactive way.”
Moreover, agents could use property and listings data to understand client preferences to deliver tailored, timely services.
“If you think about how buyers currently look for property, the search criteria are pretty crude,” Mr Gray said.
“In the future, it could be that if the buyer likes the look of a kitchen in a house for example, they could ask to see other houses with similar kitchens. They could also search for houses that meet their criteria but are not currently on the market but could be in the future if the circumstances were right.”
Mr Gray’s comments have come ahead of the REB ReInnovate event in Sydney this week, where he will address how agents could harness the power of big data, artificial intelligence and machine learning to target clients and deliver bespoke services without sacrificing time, and effectively position their products.
Agents could also use data to understand the preferences of vendors considering selling their property in the near future to deliver tailored, timely services.
“If you’re a national brand, being able to do this on scale 365 days a year is where the opportunity lies,” Mr Gray said.
Furthermore, the property sector could use artificial intelligence and machine learning to increase efficiencies and reduce high maintenance costs, he added.
“Artificial intelligence and machine learning are already able to automate that process, predict the cost of the job, work out whether or not a landlord needs to approve the job, contact the consumer and trades people, and engage the consumer in conversation around the maintenance requests,” he said.
Artificial intelligence also has the ability to provide consumers with answers to their questions at any time of the day, even when agents may not be working.
“Real estate is probably the last bastion in the global market that operates in the traditional nine to five hours because we are currently reliant on people to do everything along the customer journey,” Mr Gray said.
“However, the peak time that people want to talk about property in Australia is at night. Artificial intelligence enables customers to have their questions answered at 10 o’clock at night if needed when the industry is not working.
“The customer experience will become richer and richer.”
Mr Gray encouraged real estate agents to embrace big data and artificial intelligence and “not be afraid of it or ignore it”.
“It’s already happening but it’s just about how fast it gets deployed across the industry before it becomes ubiquitous. Like any technology, first movers get the disproportionate commercial benefit.”
Jeff Gray will be elaborating on how agents could capitalise on big data, artificial intelligence and machine learning at REB ReInnovate on Thursday, 3 March.
Click here for more information about the event.
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