Why real estate sales are so hard
Real estate sales are hard. It’s even hard to argue with that. The current home buying or home selling process is enormously costly and time-consuming. But there is a hope that AI for real estate sales can change this.
On average, it takes 4.3 months to buy a home, and 2.8 months to sell. Zillow and others changed real estate transactions by empowering the buyer with information as they start searching for home to buy or listing homes for sale. This put consumers firmly in the driving seat.
For the last ten years agents almost give up their role in the most essential part of the home buying process: listing search and advise. And this put agents and brokers in position when they need to change not to be replaced. Data and technology is the key to that change.
In many real estate brokerages, data analysis teams are flooded with a never-ending stream of one-off data requests. However, this option is not available to every agent but is essential for everyone, who is working with buyers.
And what is more important, home buying or home selling is a very personalized process. That is why it is really hard to use generalized data to support this kind of decisions.
That is why we created Propertymate’s AI-powered matching.
What is the value of the matching
We analyzed more than 600,000 properties and tens of thousands of home buyers to understand their decisions. Why James liked this apartment, though it was over his budget? Why Jessica closed on a condo in DUMBO, but before that, she was only looking on Tribeca and SoHo? We tried to understand what is “this might be my future home” feeling and turn it into the data.
We figured out, that if we dig into listing data, descriptions, photos and locations of listings, we could see some pattern to understand what is important for every buyer personally.
This is how our matching was born. We learned how to analyze all relevant listing data, learned how to understand priority. Also, finally, learned how to assign this data we got to homebuyers and properties with the help of Machine Learning. Oh, and we learned how to do it on a massive scale!
So, in our case, “AI for Real Estate Sales” is a mix of a few Machine Learning tools and techniques that allow us to match all agent’s contact base with all listed properties on the market instantly. Helping them to find the ideal home for each of their clients in the fastest way.
How does the real estate matching work
At the end the use case is quite simple:
An agent has captured a potential buyer and now has to find propositions according to the buyer’s needs. In Propertymate, the agent has access to all properties on the market, and we help narrow it down before manual selection process at the end. Using Propertymate the agent can do it in seconds, and focus more on communication and closing the deal.
When you think about this kind of calculations we do to provide every Propertymate user with this data, it is hard to imagine this as an easy and simple solution, but as all that matters is agent experience, we tried to fit it in a very simple way.
With the industry’s highest-fidelity account and buyer/home matching algorithms, customizable tiebreakers, and automated contact creation agents can rest easy that CRM contacts from marketing and sales activities will automatically end up in the right place in Propertymate. Once matched, Propertymate.ai leverages the power of AI to analyze sentiment, detect buyers interests, and enrich contact data to both solve for matching business and personal contact resolution and supercharge data.
If you want to try yourself how AI in real estate sales can improve your real estate business, sign up for a free trial of Propertymate or email us at team@propertymate.ai.
Also, we wrote an article about five ways how AI helps real estate agents previously.
