How Artificial Intelligence is Used in Real Estate | Dotloop

What’s Working and What’s Not in Artificial Intelligence for Real Estate

Dan Foody

Dan Foody

October 12, 2021 | comments

How Is Artificial Intelligence Being Used in Real Estate Today and Where Can Brokerages Find Opportunities in the Future?

With all the talk of artificial intelligence (AI) recently, you’d think it was a new invention. However, the core algorithms behind modern AI (sometimes called “deep learning“) were actually invented in the Sixties.

Two things have changed over the last few years that have led to AI finally becoming useful:

  1. Access to vast amounts of data to learn from — one Google model has 1.6 trillion (yes 1,600,000,000,000) different parameters that control it — using, essentially, all the text on the Internet.
  2. Computers capable of processing all that data fast enough

Here’s a look at how AI will change real estate moving forward and what you can do to use it to your advantage.

Changing the Playing Field in Artificial Intelligence

There is a wealth of data on sold and on-market houses available if you can take advantage of it. But, even with MLS data, you need to be careful. Listing descriptions are intentionally designed to exaggerate the benefits of a property while diminishing their weaknesses. That cozy home just steps from downtown might look great but actually front a noisy street. Or maybe not.

How can Artificial Intelligence tell the difference if you can’t? The answer is that you probably look at the photos to figure it out. If you know how to look at photos in the right way, you can get a much more objective read on a home. There’s no reason that AI can’t be trained to do the same.

With enough history, AI can be trained to examine listing photos to figure out what aspects of a home make it generate more leads and what aspects make it sell for a higher price.

Imagine AI that you feed with pictures of the home and then it suggests home renovations that will increase the sales price by an additional 20%; help you write a better listing description; and pick the best photos to include in your listing.

We’ve hardly scratched the surface of what can be done to improve the sales process with AI.

How Brokers Can Gain Competitive Advantage Through AI

How can a brokerage get a competitive advantage? Let’s play a game you’ve probably heard of before: Six degrees of Kevin Bacon. Say you were a brokerage with about 2,500 agents based in New York City. Odds are that almost every seller of a home or condo in the area knows one of your agents directly or, worst case, by a friend or acquaintance through their sphere of influence. For purposes of AI, let’s talk about this as relationship data.

As an individual agent or small team, relationship building with your sphere of influence — for example via Ninja Selling — is one of the most effective strategies for business growth.

But as a brokerage, you can do better. You can build a competitive advantage by bringing together the relationship data of all of your agents. This creates a network effect. If you double your number of agents, the value of your relationship data doesn’t just double; it increases by many times in what’s called an “order N-squared” increase. That’s the nature of a network effect.

So what can you do with this competitive advantage? Here’s just one simple example: Imagine a lead comes to your website. Normally only 2-3% of Internet leads convert. But if you could use AI to route those leads to one of your agents with the strongest personal relationship to the prospect, you could increase your conversion ratio by 5x, because there’s still no substitute for a strong trusted personal relationship. And, what does this 5x improvement in conversion cost you? Zero.

Of course, all of this needs to be done in a way that builds your competitive advantage without sacrificing the individual privacy of your agents or their sphere. Nevertheless, relationship building is your unique competitive advantage, and AI can certainly help.

New to dotloop or Cloze?

Dotloop, the leading transaction management software for real estate professionals integrates with Cloze, a smart CRM with built-in Artificial Intelligence that eliminates data entry and helps real estate pros close more business.

How AI Can Work With Your CRM to Enhance Productivity

The data needed for relationship AI is most often associated with CRMs. It’s the “communication paper trail,” the records of emails, calls, text messages and meetings that creates the foundation for understanding the relationships among people.

However, the unsaid truth about most CRMs is that their records are spotty at best (and that’s being generous). Only a small percentage of agents are organized enough to make sure all records are manually entered in their CRM — and even then they are usually only a subset of the full communication paper trail. Bottom line: You can’t build useful AI on manually entered data.

As a foundation for relationship AI, you need a CRM for your agents that can automatically log all inbound and outbound emails, calls, text messages (even ones on your mobile phone), meetings and more. This gives you a true record of communication.

With the “communication paper trail” automatically logged, there are also many great things you can do with AI to make agents more productive. For example, with Cloze CRM we use AI to automatically update contact information; remind you of important messages you might have missed; suggest the best contacts from your sphere of influence for follow-up (no manual tagging needed); and automatically classify and organize contacts.

Artificial Intelligence, when properly applied to CRM, becomes a win not only for agents by eliminating busy work and helping them to be more productive and organized, but also a win for your brokerage.

Dan Foody, Co-Founder of Cloze Real Estate CRM

Dan Foody

Dan Foody is co-founder and CEO of Cloze, a real estate CRM and AI personal assistant in one. Dan has been building products based on AI and natural language processing for over 10 years. In addition, he is a world-renowned expert in distributed systems and integration.