In this episode of the Multifamily Innovation® Podcast, part of our Meet the Partner series, we explore the transformative impact of AI in the multifamily industry with Eugene Keplinger from LeaseHawk. With a robust background in engineering and product management, Eugene brings a rich perspective from his experiences at American Express and Invitation Homes.
Eugene and Patrick discuss the strategic use of AI to improve interactions between multifamily operators and their residents. Eugene provides insights into the importance of data in tailoring resident experiences and how LeaseHawk leverages vast amounts of call data to refine customer service strategies and drive resident satisfaction.
Eugene addresses the broader implications of AI in the industry, including the challenges of adopting new technologies and the potential for AI to revolutionize resident engagement. He emphasizes the need for a balanced approach to integrating AI, highlighting its capacity to enhance service delivery without replacing the human touch entirely.
The episode wraps up with Eugene reflecting on the future of AI in multifamily operations, focusing on the ongoing need for innovation and adaptation to meet evolving resident expectations. He underscores the significance of continuous learning and staying ahead in technology to maintain competitive advantage and improve the quality of resident interactions.
Eugene Keplinger's insights underline the critical role of AI in shaping the future of the multifamily industry, from streamlining operations to enhancing resident interactions. His forward-looking approach provides valuable lessons on leveraging technology to build more connected and responsive community environments.
About the Multifamily Innovation® Council:
The Multifamily Innovation® Council is the executive level membership organization that makes a difference in your bottom line, drives a better experience for your employees, and allows you an experience that keeps demand strong for your company. The council is uniquely positioned to focus on the intersection of Leadership, Technology, AI, and Innovation.
The Multifamily Innovation® Council is for Multifamily Business leaders who want to unlock value inside their organization so they can create better experiences and drive profitability inside their company.
To learn more or to join, visit https://multifamilyinnovation.com/council.
For more information and to engage with leaders shaping the future of multifamily innovation, visit https://multifamilyinnovation.com/.
Connect:
Multifamily Innovation® Council: https://multifamilyinnovation.com/council/
Multifamily Innovation® & AI Summit: https://multifamilyinnovation.com/
Patrick Antrim: https://www.linkedin.com/in/patrickantrim/
Speaker 1: All right, welcome back.
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We're here in our studio with Eugene Koepplinger.
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He is the head of product for LeaseHawk and very well versed
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in AI and all the things that they're doing to build
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interesting and productive products for companies and
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multifamily.
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This is part of our Meet the Partner series.
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Leasehawk has been around doing AI and innovating the
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multifamily space for many years and we'll get to know Eugene
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and what you're working on.
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Speaker 2: Yeah, thanks, thanks.
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I'm really excited about it, really excited about the
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opportunity to talk about AI and how it impacts multifamily
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industry.
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Speaker 1: Yeah, you know, I'll tell you at the beginning, and I
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want to let those that are executives trying to figure out
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what to do with this and how to actually bring AI into the
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business, because obviously there's a lot of conversation
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around it and there's many software tools that are
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introducing AI that maybe haven't before, and it's going
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to be everywhere.
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There was an event that I thought was interesting around
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AIR, which is AI is everywhere, just like AIR, but you guys have
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been native in AI for many, many years.
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I'd love to dive into your background a little bit more and
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what inspired you to come to LeaseHawk to make what's next
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for what you guys are working on .
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Speaker 2: Sure sure so I'm going to step in the way back
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machine working on.
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Sure sure so I'm going to step in the way back machine.
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I've been in the engineering product management space for
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quite some time and I've learned over the years, through product
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management methodologies, that understanding business problems
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and solving those business problems using technology is
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really at the forefront of every business that's out there.
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And so I was lucky to get drafted by a friend a prior
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friend and colleague, larry into LeaseHawk using the same
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methodologies that I've been using for a long time in product
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management to help solve those business problems.
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Speaker 1: Yeah, and going back, that was even Invitation Homes,
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correct.
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And then, even before that, you spent some time with American
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Express.
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Speaker 2: Yeah.
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So I was at Invitation Homes and then American Express, and
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then Larry said let's get the team back together, and so we
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went over to LeaseHawk to keep moving on the vision that we had
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had for a long time, which is how can we leverage technology
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to solve business problems in the multifamily and
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single-family space?
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Speaker 1: You know, I'll tell you, american Express is one of
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my favorite brands just because not only being a member, right,
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you're this cardholder member and that whole experience.
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I mean we're using a lot of the strategies that they've used to
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build a business that we use to build ours.
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I mean you think about how they support business owners and
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small businesses and you know we think of them as credit cards,
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but really they're more than that, right, I mean it's.
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And data management.
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Speaker 2: You know, I was at American Express for a while and
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the number one focus that we had was making sure that client
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data was secure and protected and accurate.
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That was the number one focus for every department within the
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company.
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Speaker 1: Yeah, and partnerships too, make me I
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think about a lot of partnerships, even from venues
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and concerts.
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And, you know, make me I think about a lot of partnerships,
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even from venues and concerts.
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And you know, when you look at brands like data or companies
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that respect data in that way, like Tesla, let's say,
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innovative brand and easy to pick on, right, but no company
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is really Tesla.
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We don't have like an Elon Musk in our industry.
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Arguably you would say Mike Mueller would be that right.
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Speaker 2: Oh for sure.
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He's definitely pushing the boundaries, just like Elon Musk.
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Very similar tactics.
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Speaker 1: Yeah, and so what I mean by this, though, is, if you
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think about data in Tesla after that product is shipped, I
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guess they know everything that's happening after the sale
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as much as before the sale, right, how that product is being
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used.
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But I like the idea of the partnerships that's happening
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with Amex, knowing, like, when you look at a Tesla, they're
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trying to increase the value of the vehicle instead of just the
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price, right?
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So most of the automakers like how do we sell more at a higher
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price, at a higher margin?
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And Elon's thinking like, how do I make the vehicle more
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valuable to the customer?
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And I look at Amex or American Express that way, where there's
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a premium for fees on certain cards, but the value with these
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partnerships is more valuable than other cards in its
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comparison, right.
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So if we can think about bringing that back to
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multifamily, how do you make the lease more valuable?
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Right, using data and the customer experience and all
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those things.
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It just makes me think about how important technology
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companies in multifamily need to , I think, bring in leaders like
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yourself that have this type of background and experience to
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then innovate inside multifamily companies.
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Speaker 2: Yeah, I think you hit on a key point, which is adding
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value.
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I think that every successful company has grown their success
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based on the value that they're bringing to whatever community
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they're serving.
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And in Amex you brought up the point of partnerships and safety
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around data and data management .
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They're looking at the data to find out how can they make the
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product more valuable, and that ends up generating a stickier
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product.
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It ends up increasing customer satisfaction and then it gives
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you a landing platform to really start innovating and creating
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new products that add additional value.
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Speaker 1: You know you mentioned adding value.
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I got to take me back into the decision of joining LeaseHawk.
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What did you see as a way that through your background and
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product and data and these amazing organizations, you've
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helped change and grow?
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How do you see that decision?
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Like?
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Where did you think you would add value at?
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Like a company like Leesock?
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Speaker 2: Oh, great question.
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So, um, I I really learned a lot about the industry at
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Invitation Homes, um and and, and actually that I was over at
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a company called DriveTime.
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Drivetime was a major investor in Carvana before Carvana
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actually took off and became a private company or a public
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company.
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And when I migrated from that, from the car sales industry,
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into the single family industry, what I noticed was how many
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different items were exactly the same.
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You're replacing the number one purchased thing, most expensive
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thing, which is a house with a car right, your number two, most
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expensive thing.
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Sure, you still have the amount of risk for making sure that
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your prospects are the right prospects to buy the vehicle.
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And same thing for a house.
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You're taking risk on that consumer.
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And same thing for a house You're taking risk on that
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consumer.
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And so there was so much overlay between the two
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industries that when I got a chance to go over to Invitation
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Homes, I learned that.
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And then when Larry went over to LeaseHawk, I was jazzed at
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taking all of the experiences that I learned around Carvana,
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drivetime and Invitation Homes and applying that to the
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multifamily space.
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I would say that the multifamily space is probably
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five to eight years technologically behind the car
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sales industry.
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What I found interesting is when we were building out the
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Carvana model, we had this concept of people can do it
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automatically through self-service.
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And I remember thinking to myself no way, everyone wants to
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test drive a car, they want to go see the car, they want to
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touch the car.
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I was boldly wrong, it was.
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It was.
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They are 100% right that the industry is moving towards
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self-service and automation as fast as possible.
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One thing we can do to reduce the amount of barriers that a
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consumer has to go through to gain access to their product and
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let them conduct business at whatever time they want to.
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If they have to start work at 5 am, that means they may want to
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wake up a little early and start doing some shopping for
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their next apartment community.
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Let them do it and don't make them pick up the phone call and
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call somebody.
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Let them do it online.
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Let them do it via text message .
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Anything that we can do to increase self-service and
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automation is key for the industry.
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Speaker 1: Yeah, I mean you begin to think like a lot of the
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jobs were nine to five jobs the customer, the renters, right,
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and that whole global workforce is changing, I would suspect,
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even more and more as time goes on and it's just not enough to
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be able to.
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I mean, who said our offices needed to be open?
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Between these times Like this is, when does commerce actually
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happen?
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That was before you were able to do.
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You know things online and research online and reviews and
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all these types of things you know.
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From that aspect, how are you testing assumptions, like I
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would imagine?
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One of the things I hear inside the innovation council is you
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know a lot of the um, a lot of the organizations have achieved
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so much success with the old model, and I would.
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I would.
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I would relate to the automotive industry, where you
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have the large organizations and national chains and you know
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that are more invested in scale and franchise model.
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Then you have, like the small, you know, dealership rooftop in
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Delaware and that owner has done really, really well with the
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old process.
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You know, and it seems like the technology's here to solve the
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business problem.
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There needs to be, in many cases, a shift in behavior to
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either open your mind to something new or test the
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assumption about something.
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How did you get through the testing, that assumption of even
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yourself, like with the car model, even?
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Speaker 2: Yeah, were there others that had that feeling and
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pushed back.
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And what data did we need to feel like you know what, this is
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something that could work at scale, yeah, and then you
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monitor what happens afterwards and that's applicable to every
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industry.
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And so the whole Carvana model similar right.
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They had this idea, they rolled it out in a very small market
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and they waited and saw what the data looked like.
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How many people were buying cars, was it better or worse
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than the original benchmark that they had using their standard
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business problem or process?
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We kind of do the same thing at LeaseHawk, where we have this
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new concept, this new idea, and we look for really innovative
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companies that want to partner with us to apply these new
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concepts and theories and let's let it bake and let's see what
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happens and let's compare the output of those experiments to
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the original benchmark and and what we're finding is that
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consumers are actually, once you open up those floodgates,
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consumers want to do business differently than the nine to
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five model that we originally had.
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Um, they they may not want to just on the phone.
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They don't want to pick up the phone and talk to somebody
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because they have no idea how long they're going to wait on
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hold.
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They have no idea what's going to be on the other side of that.
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They have no idea what kind of mood the other person's going to
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be in.
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And so, the more that we can allow them to do self-service on
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the channel that they prefer text message, phone call, chat
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you know those letting them conduct business on the terms
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that they want to, at whatever time that they want to we see a
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lot of value add.
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You know, when we look at the data of some of our clients, we
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see that people are conducting business outside of the 5 pm
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time.
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You know the business hours of 9 to 5.
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We see people conducting business via text and chat at 6
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o'clock, 7 o'clock and then on the chat channel, which is on
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websites, that productivity continues until 12 or 1 in the
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morning.
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People are conducting business at 12 or 1 in the morning, which
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is way outside of the benchmark of 9 to 5.
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And you don't want to not have those customers.
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You want to give them the access to conduct business at
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whatever time they want, using whatever tools they want, and so
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we're seeing a lot of value in letting the consumer drive how
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they want to conduct business.
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Speaker 1: Yeah, it makes sense.
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I mean, you mentioned data and I start to think about, you know
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, the clients sometimes make decisions based off of their own
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confirmation bias or their own bias, and in many cases it's
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they.
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They're not, they may not even be the customer right.
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So when you think about um, the you mentioned earlier around
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forward-thinking brands and innovative brands that want to,
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you know, do this.
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The reality is that's not even the case anymore.
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Right now, interest rates are beyond something that we can
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control.
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Insurance costs is out of control, rising in double digits
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.
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You've got utilities going up.
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You have payroll going up, employee turnover going up,
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training, retraining going up.
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You have payroll going up, employee turnover going up,
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training, retraining, the maintenance costs.
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We have to find other paths to income and this is not only an
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assistance program where it can give you more productivity in
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your business, but also, I think , take out some of the expense
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that we're spending on missed opportunities and if you
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mentioned, sales and that type of stuff.
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But going back to the data, one company makes a decision, they
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have their data for their company and their portfolio, but
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you guys have it for a wide, wide net, very long years, and
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that seems to be the compelling piece in AI today is that you
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can't catch up with that type of data set right 100%.
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So when you walk into a meeting with a client, you can help
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them in a more diverse way, knowing that data.
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Can we lean into a little bit about what you're learning with
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that data today?
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Speaker 2: Yeah, I would say that we've got more data around
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properties and consumers of those properties than most
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companies.
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You know LeaseHawk.
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We've been around for quite some time.
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We've been using AI for a long time.
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We've recorded over gosh I don't remember what the last
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number was over 100 million phone calls and that's a ton of
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data around consumers and residents that are calling a
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property.
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And so now, when we overlay AI, on top of all of this
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communication that's coming to these properties, we can really
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get some interesting insights around.
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What are prospects calling for?
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What are residents calling for?
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What's driving them to pick up that call and call you?
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What times are they calling you ?
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Who's answering these calls?
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And so we can now give you an extra layer of insights into
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your property and your consumers that most people don't have.
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I think that the most powerful data set that we get is consumer
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questions, because the prospects call in and they
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interact with a LeaseHawk product of some sort and we
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analyze that data.
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We're getting an unfettered data set of what is driving their
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demand, what are their buying decisions.
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I know I've been asked by a lot of marketing people what are
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people asking about?
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How do I need to adjust my marketing?
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We all know that pricing and availability is the number one
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question that gets asked, but do you know what's number two?
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Do you know what's number three ?
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Do you know what's number four?
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We can give you the list of all of the questions that consumers
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are asking, and what's great is it's unbiased.
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The consumer doesn't even know that they're giving us access to
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this data just by asking the questions that they're asking,
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and so we can now help properties really adjust their
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marketing and positioning or solve resident-based problems,
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because a lot of the calls we take are residents as well.
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They're calling in trying to find out what the link is for
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their work order forms or to schedule amenities or complaints
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of some sort, and we can now take action on all that data and
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do something about it and create new workflows, new
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automations new workflows, new automations.
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Speaker 1: How has your experience back, even going back
00:16:54
to American Express and these other brands?
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How has that shaped your meetings and as you're designing
00:16:58
and working through these conversations internally with AI
00:17:01
?
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Speaker 2: Yeah, great question.
00:17:04
So what's funny is I'm going to actually take the AI part of
00:17:07
that question out of the equation, because the process
00:17:12
for developing new technology is the same process.
00:17:14
It's been since forever.
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It is let's understand the business problems, the really,
00:17:21
really pervasive problems that companies are having, and what
00:17:24
technology can we leverage to help solve those problems.
00:17:27
And so when we talk about all these previous brands of Amex or
00:17:34
Invitation Homes, the process in innovation has always been
00:17:41
the same, which is let's go talk to our clients, let's go talk
00:17:44
to the users of this technology and let's find out what they're
00:17:48
using it for.
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What problems do they have?
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What additional problems do they have that have nothing to
00:17:54
do with our industry?
00:17:55
And once you really understand your consumers and what problems
00:18:00
they have, that's when you can start thinking about technical
00:18:03
solutions to help solve those problems.
00:18:07
What I've learned over the past seven, eight years is that AI
00:18:12
tends to be on the forefront of my thought process.
00:18:15
When I'm thinking about technology to solve the problems
00:18:17
, um, but it doesn't have to be the number one solution to every
00:18:21
single problem.
00:18:22
In fact, we know that's not the case.
00:18:23
Yeah, um, but uh, but I do find myself jumping more towards
00:18:28
okay, how can ai help me solve this problem?
00:18:30
And then I have to work my way back and say, um, that's not
00:18:33
really the right use case for AI , let's use a different type of
00:18:37
technology to help solve those problems.
00:18:39
But that really helps shape the roadmap and and and build up
00:18:42
our company brand.
00:18:43
Speaker 1: Right, we want our problem to go away.
00:18:45
We don't want a new thing, Right, Right, it's the last
00:18:47
thing we need, Um, and and that's part of there's a lot of
00:18:51
people that could be intimidated by these conversations because
00:18:56
they could build a building which I architectural plan, the
00:18:59
engineers, the disciplines from electrical, the infrastructure,
00:19:02
all that stuff for something to stand strong, vertically right,
00:19:23
and you have compliance to that.
00:19:25
You know city inspections and they also have a long view with
00:19:30
the process, so they respect the process.
00:19:32
The process when it comes to technology, we kind of just want
00:19:36
it right now.
00:19:38
We just want it to work and is as as um, you know, consumer or
00:19:42
business people we want.
00:19:53
Speaker 2: We want the technology to work fast and we
00:19:54
want it immediately and has to be perfect.
00:19:57
Um, uh, consumers of our products have the same exact
00:20:00
opinion.
00:20:01
They they want access to whatever they want with the
00:20:05
least amount of limitations, as fast as they possibly can.
00:20:08
Um with you know, without having to interact with people,
00:20:13
that self-service and automation is really a key right.
00:20:18
Or I shouldn't even say self-service and automation,
00:20:21
it's really self-gratification, instant gratification, right.
00:20:24
How do I get what I'm trying to get at as fast as I possibly
00:20:28
can with the least amount of mistakes?
00:20:30
I think it's just part of human nature.
00:20:32
Speaker 1: Yeah, I mean you'd think of like a delivery service
00:20:34
and just seeing that this is on your way, or Amazon, it's 10
00:20:39
steps away.
00:20:39
There's little dopamine, hits of that.
00:20:43
I'm moving towards the thing I need as a customer.
00:20:46
It's pretty interesting, and when you leave a voicemail, that
00:20:50
doesn't work.
00:21:19
Speaker 2: You're just wondering like will they call me back?
00:21:21
Because likely they won't right up that call.
00:21:23
I'm not getting that self-service that I wanted and
00:21:27
I'm not going to leave a voicemail because I have no idea
00:21:29
who's going to listen to it.
00:21:30
Speaker 1: I have no idea when I'm going to get a call back and
00:21:39
that goes against what I'm trying to do, which is how do I
00:21:41
quickly accomplish the goal that I'm trying to accomplish?
00:21:42
Yeah, it's interesting when we back up.
00:21:44
You know and I look here around , maybe you can catch me up,
00:21:49
because last time we sat down with your team it's been a while
00:21:54
and I know things move quickly.
00:21:56
Tell me how you're using AI to help sort of centralize the
00:22:02
relationship with technology, and how we communicate and
00:22:05
engage with residents.
00:22:07
What's new today that you can talk about?
00:22:10
Speaker 2: Oh yeah.
00:22:10
So you know, when we look at what LeaseHawk has been doing
00:22:14
over the last couple of years, at first we started on the
00:22:17
prospect side of things.
00:22:18
There was a really big problem to solve, which was people
00:22:22
wanted to get access to the information about the property
00:22:26
using the phone channel, and leasing agents were extremely
00:22:29
busy they were overly busy and they couldn't address every
00:22:33
single phone call that was coming in.
00:22:34
While helping this other customer go on a tour, while
00:22:38
responding to this resident complaint, while working on this
00:22:43
work order, they were just too busy, and so there's a massive
00:22:46
problem there on the prospect side of things.
00:22:48
So that's where we decided to leverage AI to help answer all
00:22:51
of those calls.
00:22:52
I mean, if you think about it, these property management
00:22:56
companies are spending lots of money to ILS companies like
00:23:01
Zillow or apartmentscom or whatever to generate leads, and
00:23:05
then the leads are picking up the phone and calling that
00:23:07
property, but if the property can't answer that call, then
00:23:11
that lead falls flat on the floor, and if you just give them
00:23:13
a voicemail, they're probably not going to leave a voicemail,
00:23:17
and so you're not even getting all the leads you're paying for.
00:23:21
So that's where we really wanted to focus in on the
00:23:24
prospect side of things.
00:23:25
But to go back to your original question, which is how can we
00:23:27
take that knowledge and that technology and apply it to the
00:23:30
resident side of things?
00:23:31
We started rolling out resident services as part of our offering
00:23:36
, which is we'll now take resident based phone calls and,
00:23:40
using AI and using workflow, we'll let residents that just
00:23:44
want simple tasks accomplished.
00:23:47
What's the link to fill out a work order form?
00:23:49
What time is the gym open?
00:23:51
Can I schedule this amenity?
00:23:53
I have this leaky toilet.
00:23:55
These are all great examples of how we could take what we've
00:23:59
already built on the prospect side of things and apply it to
00:24:01
the resident side of things, which increases the resident
00:24:05
satisfaction because they're now gaining access to the
00:24:08
information they need without having to wait, without having
00:24:11
to talk to a person, without having to leave a voicemail and
00:24:14
not know when they're not going to get called back.
00:24:16
Sure, it hits that dopamine level, like you mentioned,
00:24:20
around.
00:24:21
I just now have access to this data that I've been looking for.
00:24:24
Speaker 1: Yeah, and there's more trust there in the process
00:24:26
because they wouldn't be a resident if they didn't go
00:24:29
through that right, with LeaseHawk and that process.
00:24:31
So, you know, I think about and we've talked about this in our
00:24:35
council meetings is, you know, we're a people business and you
00:24:46
know I was speaking with NVIDIA yesterday as part of our council
00:24:49
stuff and he said look at AI as instead of artificial, look at
00:24:51
it as like assistance, you know, and I thought that was really
00:24:56
compelling because a lot of what you're doing is you're allowing
00:24:59
each leasing agent or manager, whoever's involved in the sales
00:25:05
process to have this assistant, right, but also before the sale
00:25:08
right, paying all the money for the ads you have the sales
00:25:11
assistant, but then after the sale right, but also before the
00:25:13
sale, right, paying all the money for the ads, you have the
00:25:14
sales assistant, but then after the sale right.
00:25:15
So then it's more likely to convert on a renewal if things
00:25:18
go well during this day, right.
00:25:19
So that's assisting the whole financial process there in
00:25:24
ultimately, what we're doing, which is renting apartments.
00:25:26
But there's been some pushback, even in our meeting around
00:25:31
selling and it's like if someone's not there to know
00:25:38
where the sale fell off or the objection is then how would you
00:25:44
know how to convert or follow up and that stuff?
00:25:47
And that's where I think about your data is you guys are
00:25:50
listening to all these things online, the questions and all
00:25:54
that stuff.
00:25:55
Are people using that data when they're building new
00:25:58
developments and they're thinking about the ideal
00:26:00
customer?
00:26:01
Do you guys see?
00:26:02
Speaker 2: that already, oh for sure, a hundred percent, so that
00:26:06
data is actually more valuable to us than the data of success.
00:26:11
We have a lot of data that shows all the successes of AI
00:26:17
and consumers that call in and they interact with our AI
00:26:19
technology and they schedule tours and they ask their
00:26:22
questions and they get the information that they are
00:26:25
looking for.
00:26:27
All that does is support the theory that AI can be used
00:26:32
productively by consumers, but that doesn't help us grow any,
00:26:36
and so where the data really becomes valuable is in those
00:26:40
scenarios where someone doesn't get information they're looking
00:26:43
for or immediately wants to transfer and talk to a human.
00:26:46
We can look at that data and find out oh well interesting.
00:26:51
We didn't know that people were asking these types of questions.
00:26:53
Let's go ahead and train our models to go ahead and answer
00:26:56
these types of questions.
00:26:57
Or I didn't know that that was a workflow that needed to be
00:26:59
built out.
00:27:00
The data is telling us that this consumer, you know, hit a
00:27:05
roadblock and needed help, and it was a simple workflow
00:27:09
configuration that we had to do to be able to allow them to use
00:27:13
AI to accomplish those things.
00:27:14
So it's that whole Google methodology of fail fast fail,
00:27:19
often so that you can get the data and find out what
00:27:22
adjustments you need to make.
00:27:23
Speaker 1: Yeah, it's interesting Knowing what you
00:27:25
know and knowing what's possible because you're embedded in all
00:27:30
this stuff.
00:27:31
What would you say to a multifamily owner-operator
00:27:36
executive that is looking to you , know, obviously protect cash
00:27:42
flow but also grow the business in a way that they make all the
00:27:46
right moves right, so it's safe, conservative?
00:27:50
How would you be thinking through all of this in terms of
00:27:54
that prospect journey and and like what would you?
00:27:57
What would you tell them?
00:28:00
Speaker 2: yeah, um, I think there's a lot of different
00:28:02
metrics that can support the use of ai and automation and
00:28:05
self-service.
00:28:06
Uh, to to help support my portfolio of properties, um, if
00:28:12
I were the owner operator yeah, if you're, you're theoperator,
00:28:15
it's your building.
00:28:16
Speaker 1: Now you have this tool.
00:28:18
Speaker 2: Yeah, the things that I would be looking for are
00:28:21
metrics around how much do I save by leveraging AI, how much
00:28:27
additional money do I make by leveraging AI?
00:28:29
And we've done a couple case studies with some of our clients
00:28:33
and what we found is, when AI is in use, we have found that
00:28:40
lead-to-lease time decreases by roughly 15% 20% when AI is in
00:28:46
play, and that's for same-store data.
00:28:48
So a consumer that uses AI versus a consumer that doesn't
00:28:51
use AI, for the same exact property, the consumer that uses
00:28:54
AI tends to convert faster than a consumer that doesn't use AI,
00:29:01
and that is immediate revenue to the bottom line.
00:29:04
I no longer have those marketing costs because that
00:29:09
unit is not as vacant or is not vacant for as long as it was.
00:29:12
I don't have the holding costs associated.
00:29:16
I now have additional revenue coming in a day, two days, three
00:29:20
days faster using AI, and those are really impactful for me as
00:29:25
a property owner.
00:29:26
Furthermore, when we look at what AI allows in that
00:29:31
self-service and automation, I know that I can grow my business
00:29:35
without growing my human costs at the same clip.
00:29:39
So if I can add another property without adding a
00:29:44
full-time staff for that property, because I now have AI
00:29:48
to answer 50% of the calls that weren't getting answered
00:29:51
originally.
00:29:51
That's also impactful to my bottom line.
00:29:55
I have less operational costs, uh to to manage my properties
00:30:00
and and I think both of those are really good metrics to to
00:30:03
look into if I was a property property owner people have and
00:30:06
also the priorities to those.
00:30:08
Speaker 1: So, as you map that out in spoken word, I'm curious
00:30:23
how do you take that back to meetings and roadmap even your
00:30:25
own product design so that it's aligned with these?
00:30:26
Speaker 2: types of initiatives you just described.
00:30:27
Yeah, I mean, if I look at LeaseHawk's vision, our vision
00:30:30
is how can we increase the speed of leasing and increase the
00:30:40
consumer experience for what we call our leasing lifecycle?
00:30:44
So that is not just searching for a property and touring a
00:30:48
property, it's all the resident side of things as well.
00:30:51
That's part of the leasing lifecycle, and so we're trying
00:30:55
to, and so we're trying to increase that experience through
00:30:59
self-service and automation, and what I'm finding is that the
00:31:03
ramifications of increasing the consumer's ability to gain
00:31:09
access and accomplish whatever they're trying to accomplish
00:31:14
directly impacts the bottom line from the property owner side of
00:31:18
things.
00:31:18
So I think it's a win-win for both sides of the equation.
00:31:22
The consumer's happier because they're able to conduct business
00:31:25
at whatever time that they want to, using whatever channel they
00:31:28
want to, and the owner-operator is happy because they're able
00:31:31
to lease units faster.
00:31:34
It's truly a win-win.
00:31:36
And so, when we look at our roadmap and what LeaseHawk's
00:31:40
trying to do, we want to keep increasing the amount of
00:31:44
workflows that we have using AI.
00:31:46
We want to gain more insights into our data so that we can
00:31:51
give that to properties to make better business decisions on
00:31:55
their side.
00:31:55
The whole, the whole concept of a nine to five on Monday
00:32:00
through Sunday was a thing, but using data, we've been able to
00:32:04
show that you may not have to have your office open as much,
00:32:08
because we're now able to address most of those calls on,
00:32:11
you know, friday, saturday, sundays.
00:32:13
So you now have the ability to reduce your expenses by closing
00:32:18
your office earlier using AI.
00:32:20
And again, the consumer's happy because they're getting access
00:32:23
to what they're trying to accomplish on a Sunday without
00:32:26
human intervention.
00:32:27
Speaker 1: Yeah, we've talked about this even in our meetings
00:32:30
around.
00:32:30
Even the experience, the employee experience too, like
00:32:32
giving them more flexibility in how they want to show up to work
00:32:35
so you could shut down on a Tuesday but still have fast
00:32:40
leasing speed to lease all that stuff.
00:32:42
I love how you described that.
00:32:44
You know the word automation.
00:32:45
I think of automation and then I think of autonomous.
00:32:48
Autonomous is like complete.
00:32:50
You know hands-off automation where people begin and end the
00:32:54
process.
00:32:54
You have this sort of turnover to.
00:32:56
You know there's still the hands on the steering wheel.
00:32:59
I was.
00:32:59
Have you been on a Waymo ride yet?
00:33:02
Speaker 2: I have not.
00:33:03
No, I'd be all for it, though as a technology guy, I'd be in
00:33:07
no problem.
00:33:11
Speaker 1: I did a video with it .
00:33:12
It's pretty cool.
00:33:12
I hope I'll be sharing it soon, but the steering wheel's still
00:33:14
there, you know.
00:33:15
So we're in this state of change where a lot of executives
00:33:22
worked in a way that these things weren't possible.
00:33:25
So you know, we get a job, we get promoted, we tell others how
00:33:29
to do a job, and we make great money and success and people
00:33:34
tell us we're doing great.
00:33:35
So there's this bias that we have to the path of success or
00:33:42
yields.
00:33:42
And yet here we're in this transition.
00:33:45
I've said this before.
00:33:46
We're in moments of and AI is probably accelerating it faster
00:33:50
than anything else which is the cordless phone, the self-driving
00:33:55
car, right, you know, you look at motion pictures, all these
00:34:00
things that the process changed, but we described it as
00:34:05
something that it used to be for us to just kind of have context
00:34:08
over it.
00:34:09
You know, what do you think the future of leasing is?
00:34:13
You know we don't make predictions.
00:34:15
I don't expect you to make predictions, but where do you
00:34:17
think things are going with this process?
00:34:20
Speaker 2: Yeah.
00:34:20
So I think that you've hit on a couple of components that are
00:34:24
really important.
00:34:24
Number one is that whole steering wheel.
00:34:26
When it comes to automation, I think that that's part of the
00:34:30
FUD factor the fear, uncertainty and doubt and you know, waymo
00:34:35
puts that steering wheel in place because it makes humans
00:34:39
feel better that they're in a car that has a steering wheel
00:34:41
versus not in a car.
00:34:43
It makes them trust the technology better.
00:34:44
I think that in this industry, we deal with the same kind of
00:34:49
FUD factor.
00:34:50
Now I've noticed over the last five years of being in AI in the
00:34:57
multifamily industry that that FUD factor is reducing every
00:35:01
single year and people are becoming more familiar with this
00:35:05
technology and, okay, with deploying it and trying out new
00:35:10
use cases of this technology.
00:35:12
I think there's a lot of synergies between that Waymo
00:35:16
experience that you had and using AI in our multifamily
00:35:21
industry.
00:35:22
Speaker 1: Yeah, you know, I wrote down a few things here.
00:35:24
Going back to my ride in Waymo, when I opened the app I thought
00:35:30
first I'm like, okay, I'm gonna get into this cool technology
00:35:33
thing.
00:35:33
But when I opened the app I thought, oh my gosh, that's the
00:35:35
most brilliant marketing message I've ever seen.
00:35:38
And when I opened the app it said I summoned the car and it
00:35:43
said the most experienced driver is on the way.
00:35:48
And I'm thinking about all the data and all the conversations a
00:35:51
hundred million, you said yeah, over a hundred million.
00:36:00
You said, yeah, like the most experienced leasing agent is is
00:36:02
here, right, you know, like the data I I thought, like wait a
00:36:03
minute, my car is sitting out there right now not driving.
00:36:05
This thing has been driving millions of miles, all it's
00:36:11
driven more than me.
00:36:12
You know what I mean.
00:36:13
And so we, the fear, uncertainty and doubt thing, uh
00:36:16
it thing.
00:36:17
It's more of a personal movement of self changing
00:36:21
behavior that I think plays out in these experiences.
00:36:25
Speaker 2: Yeah, for sure, I think one of the things that
00:36:26
we've had to do with our technology.
00:36:28
Because AI is again so impactful and so powerful to
00:36:35
assist our clients in getting over that FUD factor, we've had
00:36:38
to put configurations in place that say, okay, we can do this
00:36:43
as much as you want.
00:36:44
So we've got the ability to put AI up front and our technology
00:36:49
just picks up the phone and says how can I help you?
00:36:51
Right, there's no IVRs in place , there's no, you know, press
00:36:58
this if you're that.
00:36:59
It is just someone picking up the phone call every single time
00:37:03
consistently and saying how can I help you?
00:37:06
Now we can deploy it in that capacity.
00:37:09
Some of our clients are all for it.
00:37:11
They want to reduce their operating expenses as much as
00:37:13
possible, and that is a big way to do.
00:37:16
It is putting AI up front.
00:37:19
In the experience, other consumers they still like that
00:37:21
white glove approach of having a human.
00:37:24
That's there, right, that's that steering wheel in the Waymo
00:37:28
, and so we also have the ability to deploy our AI
00:37:31
technology as just a fallback, if the agent doesn't answer the
00:37:35
phone, let's go ahead and take that.
00:37:37
Call back, um, and we've we've done this so that we can get
00:37:41
through all this, these different variations of fud
00:37:44
factor is that like the crawl walk run kind of yeah, approach?
00:37:49
Speaker 1: yeah, that's right.
00:37:49
Just some more clients want to just run.
00:37:52
Speaker 2: Someone want to run and we're all for it.
00:37:54
Those, those are great, great clients of ours.
00:37:56
In fact, they ended up being the most successful clients
00:37:58
because they reduced their costs .
00:38:01
Their consumers have a great experience, a consistent
00:38:04
experience, and we get a ton of data out of it which helps us
00:38:09
train our models even further and grow our product offering.
00:38:13
Speaker 1: What are some challenges you're excited about
00:38:15
solving?
00:38:16
I can imagine AI is not done right.
00:38:20
Speaker 2: No, it's in its infancy.
00:38:22
It really has, even though we're one of the leading vendors
00:38:28
for AI in this space.
00:38:29
Even we see that it's in its infancy infancy.
00:38:39
I think the most exciting challenge that I see coming up
00:38:40
is what we call crossing the chasm.
00:38:41
If you're familiar with that book, we've seen over the last
00:38:43
five years early adopters of this technology and people that
00:38:46
are willing to experiment and deploy and test and see what
00:38:51
happens.
00:38:51
Those are what we call the early adopters.
00:38:54
Now we're kind of in this crossing the chasm moment where
00:38:58
we're going to start getting an influx of the majority of people
00:39:03
now getting comfortable using AI technology and deploying AI
00:39:07
technology across their portfolio and I think there's so
00:39:12
much growth that we'll gain out of it.
00:39:16
But also the amount of data that we'll collect out of 80% of
00:39:21
properties starting to deploy this technology and seeing what
00:39:25
comes of that data.
00:39:26
How much more automation can we input?
00:39:29
We're actually looking at using AI now to make recommendations
00:39:34
so we can analyze calls and say your leasing agent did great at
00:39:39
the introduction side of things but kind of fell flat on the on
00:39:43
their close of of these calls.
00:39:45
Here's some recommendation.
00:39:46
Here's some training material, that that we can offer to that,
00:39:50
to that agent to help them close .
00:39:52
So we're now letting AI make humans better in doing their job
00:39:57
.
00:39:57
I think that's a huge area of opportunity.
00:40:01
Speaker 1: Yeah, and I'm excited for the residents.
00:40:03
Honestly, with that data, I mean, you start to think about
00:40:06
just the way I live my life and I know people have my data
00:40:10
because things that are more interesting are coming to me
00:40:14
more naturally instead of friction in the process, even
00:40:18
from purchasing e-commerce stuff .
00:40:20
Right, I mean, the buyers have all been trained on the
00:40:26
expectations of this stuff.
00:40:27
We've covered a lot here.
00:40:29
I want to make sure that I don't miss anything.
00:40:31
What you know about the ability for you to come into an
00:40:39
organization, bring AI, bring technology and solutions to
00:40:41
lease faster what, what?
00:40:42
What did I?
00:40:42
What?
00:40:43
What did I miss?
00:40:44
Is there something that I should have asked that I didn't
00:40:46
ask?
00:40:47
Speaker 2: Um, no, I don't think so, but but I do.
00:40:50
I do want to leave one statement, which is um, you know
00:40:54
, ai is, is, is.
00:40:55
Ai is great technology, but it's not the answer to
00:40:59
everything by itself.
00:41:01
It's no different than a Swiss army knife.
00:41:03
It's got a lot of different use cases, but it's also limited in
00:41:06
its use cases.
00:41:07
So I guess my messaging would be don't be afraid of AI
00:41:12
technology.
00:41:13
Also, don't try to apply AI technology to every problem that
00:41:18
you have, because it's got its use cases where it's great and
00:41:22
some that it's not the most important technology to use.
00:41:25
And the third thing I'd say is, when you're going out and
00:41:30
looking at AI and how to deploy AI, talk to your vendors.
00:41:34
Make sure your vendors are experienced.
00:41:37
They've been in the game for a long time.
00:41:39
We've been in the game for a long time, so we can tell you
00:41:42
all of the great use cases of AI technology.
00:41:44
But also there's some areas that that technology is not the
00:41:49
most impactful and we've got other recommendations for it.
00:41:52
So I think leveraging that consultative approach with AI
00:41:59
experienced vendors is key to the industry.
00:42:03
Speaker 1: Yeah, and we're going to bring you guys into the
00:42:04
council and help our members understand more of these things.
00:42:07
Because you know, like again I go back to the analogy of
00:42:11
building apartments, because until you, you know, we have
00:42:15
these white walls in our studio here.
00:42:18
I always call them like the museum walls, like if you put
00:42:21
art on it, you know that's it increases the value of the thing
00:42:25
, right.
00:42:26
But to me, building apartments, I can see through the, I can
00:42:29
almost see through the drywall, right, because I know what's
00:42:33
behind it.
00:42:33
You know, because I know what's behind it.
00:42:35
You know, and I think as executives listen to you know
00:42:42
people like yourself and other experts that have actually built
00:42:44
things then this isn't something to just like consume.
00:42:48
You have to play with it, you have to see it used.
00:42:51
It's like when I went in the Waymo, like I experienced it,
00:42:56
and I just encourage anybody if they're in that what did you
00:42:59
call it?
00:42:59
Fud, fear, uncertainty and doubt.
00:43:01
State the way through.
00:43:04
That is jumping on a call, getting in touch with someone
00:43:07
like yourself and trying something like using it, seeing
00:43:11
the result, reflecting on the data, and that's why we're
00:43:14
bringing in, you know, someone that's leading product.
00:43:17
You know you're not here to sell.
00:43:18
You're here to help us understand this stuff so we can
00:43:21
create the value.
00:43:23
I like also the way that your vision is.
00:43:25
It's not like you're here to talk about AI.
00:43:27
We're talking about speed to lease, we're talking about those
00:43:30
efficiency programs, the profitability of that company,
00:43:34
and that can be exciting.
00:43:35
So I appreciate your time.
00:43:37
You know, I know that this is probably more of a series and,
00:43:41
again, you know the stuff that we'll do inside the council will
00:43:44
be useful in answering some of the questions.
00:43:46
Or, if you have a question, if you're listening or you're
00:43:50
watching, send us a message and we'll get it to Eugene and we'll
00:43:55
talk about what's next for you and your company.
00:43:57
But thanks for coming on.
00:43:58
Any final thoughts you want to leave our viewers with?
00:44:02
Speaker 2: No, no.
00:44:02
I'm very grateful to be in this technology space, in this
00:44:08
industry that has so many different use cases for
00:44:12
technology, and it's just a great experience for myself.
00:44:15
I love watching the market change and I really look forward
00:44:19
to where we go over the next 10 years.
00:44:21
Speaker 1: That's awesome.
00:44:22
It's great.
00:44:22
I love what you said about the due diligence when that change
00:44:25
is coming.
00:44:26
Stick with those that have been through it.
00:44:29
Speaker 2: Yeah, for sure.
00:44:29
Well, thanks so much for having me.
00:44:30
Speaker 1: Yeah, great to have you on.
00:44:31
We'll see you in the next one.
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