The aggregated data will include publicly available sales information not only from Coldwell Banker but also from other brokerages and demographic data to help flag households that are most likely to list, such as young, growing families looking for a larger home or retirees who want to downsize.

Earlier this week, Coldwell Banker announced the launch of CBx Seller Leads, a tool that uses big data, machine learning and predictive analytics to help Coldwell Banker affiliated agents identify potential sellers and convert them into clients — before these people have even expressed an outright interest in listing their homes for sale or even requested a price estimate.

“What we’ve built with CBx Seller Leads and the entire CBx Technology Suite, is all about empowering brokers and agents, so they can effectively use big data to generate more leads, close more sales, be more productive and turn a higher profit,” said Coldwell Banker Charlie Young in a statement.

Just like CBx Listing Experience, a platform that helps agents and sellers set a competitive listing price and identify potential buyers, CBx Seller Leads utilizes big data to accurately identify sellers on the cusp of listing their home. CBx Listing Experience pulled publicly available information from ESRI, Experian, OnBoard Informatics, Realtors Property Resources (RPR) and the U.S. Census Bureau to create buyer profiles.

In a phone call with Inman, VP of product marketing and communications Zoë Horneck said CBx Seller Leads will pull information from some of those same sources, but this time, Coldwell Banker will primarily rely on data culled by two, large proprietary algorithms.

The aggregated data will include publicly available sales information not only from Coldwell Banker, but from other brokerages, and demographic data to help flag households that are most likely to list, such as young, growing families looking for a larger home or retirees who want to downsize. From there, the proprietary predictive analytics tool kicks in to determine how likely a seller will list.

Furthermore, CBx Seller Leads also supplies agents with information predicting the amount of time it will take a home to sell if they list it at a certain price point.

Horneck said the use of big data and predictive analytics is what differentiates CBx Seller Leads from other tools that require agents to choose specific properties to track and only alerts them when a seller has completed a purchase loan application.

Agents then use that information to complete cold calls, which only yields a 1 percent to 2 percent conversion rate.

Meanwhile, a one-year pilot trial in 16 select markets yielded a conversion rate of 5 percent, which Horneck credits to CBx Seller Leads’ ability to generate a list of potential sellers with specific demographic and market information that agents can use to start a meaningful conversation, thus turning a lead into a client.

Knoxville, Tennessee-based agent Andrew McGranaghan said the CBx Seller Leads tool has given him back at least 10 hours a week (two hours per day) that he would’ve spent making cold calls, walking door to door and sending mailers to households who aren’t interested in selling or who have already chosen an agent.

“Instead of targeting a specific area, I’m actually targeting people who are likely to sell before they’ve expressed an interest or before other agents realize they’re likely to sell,” McGranaghan said. “So I’m able to get there first with my marketing campaign and cold calling. I’m able to cultivate that relationship and get more listings.”

“Like many places across the country, we’ve had a significant inventory shortage this year, and there are almost as many active agents as there are listings in our MLS, so it’s a very competitive environment,” he added.

Email Marian McPherson

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