BrokerageReal EstateReal Estate Tech

Brokerages turn to AI to identify leads, the right agents

“We see the most change in brokerage operations when the market slows down.”

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In August, Gary Keller told the more than 11,000 Keller Williams agents gathered in Austin, Texas for Keller Williams Mega Camp that the industry looks on track to close about 5.1 million home sales in 2022.

Historically, 5.1 million home sales looks pretty good. But compared to 2021, when 6.12 million existing homes were sold, it doesn’t look great. The forecast for 2023 looks even worse – Fannie Mae estimates that about 4.98 million homes will sell in 2023 and the economy will contract by .5%. A recession is likely.

With a one-two punch of mortgage rates and high home prices keeping prospective buyers – and sellers – on the sidelines, brokerages are closing brick-and-mortar offices, shedding administrative and support staff, and looking under every couch cushion for money to make it through the lean times.

In these times of tumult, brokerage executives are turning to artificial intelligence technology to root out potential leads buried in their agents’ CRMs. They’re also using AI to identify agents worth keeping, and those they hope to recruit from competing brokerages.

Generating leads

The utilization of AI technology in the real estate industry has been around for some time even if its usage is spotty.

“I have a lot of respect for a company called Relitix and it has been around for [six] years,” Steve Murray, the co-founder of RealTrends Consulting said. “Relitix tracks through MLS data, the behaviors and actions of agents and it uses AI to pinpoint which agents are more likely to move than others.”

You have a lot of sellers with unreasonable expectations on price and this really helps agents analyze the listing data and then put together a presentation for their sellers.

Nick Bailey, CEO And President of RE/max

Another company well over a decade ago developed tools to look at homeowner data such as income to debt ratio, how long they have lived in the house and how many kids they have, to help agents identify leads to pursue, he said.

It is one thing to have these technology tools available, it is another to put them to use.

“Agents already have all these tools, from CRMs to marketing campaign managers, but they are only effective if they use them,” Murray said.

At RE/MAX, which started offering its agents access to the AI-powered kvCORE platform after shutting down booj, its proprietary platform, CEO Nick Bailey said agent adoption of the kvCORE platform has been strong.

Bailey said that the majority of agents at RE/MAX are taking advantage of the platform’s comparative market analysis tools.

“It is the number one thing that listing agents use with their sellers,” Bailey said. “Right now, you have a lot of sellers with unreasonable expectations on price and this really helps agents analyze the listing data and then put together a presentation for their sellers.”

The kvCORE platform and the AI it utilizes is a game-changer for lead generation, Bailey said.

“Seven or eight years ago we recorded around 4.5 million transaction sides and that same year we had around 4.5 million online leads generated, so it was roughly a one-to-one ratio even though there wasn’t a direct correlation between every online lead and every transaction side,” Bailey said. “Last year, however, there were over 200 million online leads generated with six million transaction sides. So there is a lot of online activity from consumers and interest in properties, but those leads are less likely to result in a successful transaction. But the AI has been showing in our business that there are certain behaviors consumers start to exhibit if they are being a transaction ready consumer. Once agents know what clients they need to target they waste less time and are more productive.”

Compass‘ tech stack has helped agents close deals with a similar AI-powered feature it calls “likely to sell,” agents said.

If you look at how agents are typically recruited, the brokerage looks at GCI or goes by reputation, but with AI we are able to leverage historic data to predict which agents will be the most productive in the next few years.

Damian NG, Senior Vice President of Technology at Anywhere Real Estate.

“Using a list that the Compass platform generated through ‘likely to sell,’ I sent out a few emails to people already in my CRM and in just a two-day span I got four transactions and one new client through a referral,” Todd Armstrong, a San Diego-based Compass agent, told RealTrends. “Getting those was huge for me and it just took a few emails.”

The brokerage says that leads recommended by ‘likely to sell’ result in a 94% higher “win rate” for agents than the rate for properties that weren’t identified as likely to sell.

Assessing the agents

Damian Ng, the senior vice president of technology at Anywhere, acknowledges the obvious lead generation application of AI. But he and his team have chosen to focus on two very different uses of the technology.

“If you look at how agents are typically recruited, the brokerage looks at GCI or goes by reputation, but with AI we are able to leverage historic data to predict which agents will be the most productive in the next few years,” Ng said. “So this leads our franchise owners and brokers to the agents with the most potential.”

He’s been hugely successful at recruiting because he is targeting agents based on his self-developed AI.

Steve Murray, partner at rtc consulting

In order to identify the agents with the most potential, Anywhere’s AI technology examines current productivity levels of agents compared to other agents in the same area and then it creates a model to predict what the agents future productivity will look like.

“The agents we predict for strong future growth actually grow along with the trajectory we projected,” Ng said. “So having the model is great, but using the detail analytics to prove that the model is working properly is even better.”

Murray said that a broker he works with who uses AI in a similar fashion has been able to pinpoint his recruitment effort to 400 to 600 of the agents out of the roughly 16,000 in his market.

“He’s been hugely successful at recruiting because he is targeting agents based on his self-developed AI,” Murray said.

The other area Ng and Anywhere have chosen to focus their AI energy on is lead matching. Unlike AI features that help agents identify which clients are most likely to engage in a real estate transaction, lead matching works by matching clients with the agents most likely to get that specific lead to the closing table.

“In a lot of our offices, if someone just inquired about buying or selling a home, a round robin system is used, but with our AI technology we are matching these leads with the agent in the office most likely to see a successful transaction from the lead,” Ng said. “Overall, this has led to a higher close rate for cold call leads.”

It is no surprise that brokerages are looking to leverage AI right now as they attempt to get ahead as the market slows down, said Murray.

“The level of business being done now is much slower than it was in 2021 and this may be the norm for the next couple of years, which means that it is going to be a market share dogfight among brokerage companies,” Murray said. “We are going to see brokers and agents looking around for what tool they can use to get access to more clients and give them an edge in the market. This will lead to some really great innovation. We see the most change in brokerage operations when the market slows down.”

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