Your real estate CRM is the lifeline of your real estate business. When it’s properly maintained, it’s a gold mine. Unfortunately, for most agents, going through a database to update contacts doesn’t feel as productive as pounding the pavement for listings.
But, consider this: Between 10 percent and 25 percent of the contacts in your real estate CRM contain critical errors, according to SiriusDecisions, a Connecticut marketing company.
Bad data—you know, those leads with missing, inaccurate or incomplete information—could be costing your real estate business money. Not only that, but if you hope to remain in the industry for any length of time, lead management is imperative.
Yesterday’s CRM maintenance
Go online and search for advice on how to clean and maintain your real estate CRM and you’ll find tips telling you to get rid of duplicate entries, to toss those that don’t have contact information or that contain erroneous contact information (how many people named Brad Pitt really live at 123 Main Street anyway?) and to delete any leads you consider lost causes.
While that advice may have been pertinent a decade ago, it’s crazy today.
Are you willing to delete more than half the leads in your real estate CRM? Thankfully, you don’t have to—not when big data can help you fill in the blanks and keep you updated on what’s happening in these people’s lives.
It’s all about information
Stream a movie, binge YouTube videos or shop online at Amazon and you’re contributing to the more than 2.5 quintillion bytes of consumer data that’s collected every day.
That number, by the way, was determined by IBM in 2016 so it’s safe to say that it is far larger now.
All this information forms the backbone of what is referred to as “big data” and aids in the improvement of artificial intelligence.
“Big data and artificial intelligence have a synergistic relationship. AI requires a massive scale of data to learn and improve decision-making processes and big data analytics leverages AI for better data analysis,” according to the pros at qlik.com.
“Big data,” they conclude, “is the fuel on which artificial intelligence runs.”
Here’s an example.
Jake and Lisa recently became parents to a third child. The home is feeling super crowded and they decide it’s time for a bigger place.
Both Jake and Lisa spend time online learning about the home selling experience and begin to understand that their home requires some work before putting it on the market.
They both enjoy DIY and decide that many of the improvement projects they need are something they can handle on their own.
They search online for the lumber, paint and tools to get the projects underway. They’re also searching Zillow and Redfin for homes for sale, just to get a feel for the market.
Lisa then notices that her online ad offerings have changed and she now sees ads from Home Depot and Lowe’s, retailers that sell home decor and real estate investors (the “we buy ugly homes” type).
Now, imagine this data in the hands of a real estate agent. Actually, you don’t need to imagine it because Coldwell Banker is currently using it, with its CBx app.
Released in 2018, CBx supplies agents with information on homebuyers, allowing them to be “… able to see who is buying, what they’d be interested in, and what the proper approach to them is,” according to Athena Snow, Coldwell Banker’s senior manager of public relations.
Redfin uses AI to present suggestions during a homebuyer’s search of listings.
From commercial to property rentals and residential sales, brokerages across the country are utilizing big data.
What can listing agents do with this data?
“Algorithms can now go through millions of documents in seconds, looking through property values, debt levels, home renovations, and even some of a homeowner’s personal information,” claims Diana Olick at cnbc.com.
Joseph Sirosh, chief technology officer at Compass explains to Olick that “… AI helps you find the homes that are most likely to sell in the next 12 months, and it does so by triangulating all the data associated with the home, like when the home last sold, how long the owner has occupied the home, what rate the home sells at in that particular area.”
This information, especially when combined with behavioral data (such as that from Jake and Lisa) is a powerful combination.
Because of this capability, Sirosh says that “Compass agents have a 94% higher chance of winning a potential listing they target with AI than not.”
Determining the proper approach to a potential client, knowing just when to reach out and offering solutions to their current pain points is one of the pluses of leveraging big data in your real estate CRM. Another plus? It will definitely set you apart from other agents.
What happens when your real estate CRM is full of valuable, accurate information?
Consider how financially unwise it is to blanket every lead in your real estate CRM with direct mail pieces when, with the right information, you can target only those of consumers who are planning on buying or selling a home in the near future.
Not only can the use of big data help you get to these leads sooner but, by cleaning up the information in your real estate CRM, reaching out to past clients becomes brilliant.
Imagine creating focused content that specifically addresses what each of your past clients is currently experiencing.
- A blog post about current baby nursery trends for the new parents
- A newsletter article about downsizing for retirement
- The probate home sale process for leads who’ve inherited a home
- DIY home improvement projects for home sellers
- Improvements that add to the value of the home
Think of the time, money and effort you’ll save by targeting only the most-likely to transact soon in your real estate CRM.
Get more listings
Yes, it’s important to keep in touch with past clients. Nurturing leads through the pipeline is also important. Generating leads, however, should always remain part of the mix.
This is where big data really shines.
How do we know who these possible listing clients are? Through predictive analytics, which takes consumer shopping data, and combines it with homeownership tenure records, homeowner equity and other chunks of data.
Anything that can be considered a seller signal – from purchasing home improvement items to area turnover rates – is analyzed to allow you to target only the most-likely-to-sell-soon folks in your real estate CRM.
Big data, AI and predictive analytics. They are yet other ways that technology is changing the face of real estate.
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