Homes.com is leveraging artificial intelligence to transform the online home search experience, according to insights shared by Livia Sponseller and Andy Ventura in a recent conversation with HousingWire. The executives discussed how the company’s new feature, Homes AI, aims to create a more interactive and conversational approach to home searching, a process that has largely remained static for decades.
Sponseller, the Senior Vice President of Product Management at Homes.com, emphasized the need for innovation in home searches. “What excited me most about this feature is that we were looking for a way to just completely change the way that people searched for homes online,” she stated. She pointed out that the traditional use of map placards and filter methodologies had remained unchanged for years, prompting the need for a modernized approach.
The new technology introduces an interactive environment where users can engage more fluidly with the platform. Ventura, the Vice President of Enterprise Software Architect at Homes.com, noted the loss of rigid steps typical in traditional property searches. “It’s a different way of interacting with an already very powerful web application,” he explained. Users can inquire about various aspects like grocery stores, mortgage rates, or neighborhood characteristics without losing their place in the application.
The executives characterized the launch of Homes AI as a “generational shift” in home searching, driven by the integration of AI into the browsing experience rather than as a mere add-on. Ventura remarked, “Across marketplaces, AI is often like a chatbot afterthought. We felt like it should be ingrained in the application. AI and the UI are both knowledgeable of each other.” This integration allows for real-time interaction, where user actions like changing a filter or moving a map are acknowledged by the AI.
Sponseller mentioned that the conversational model enables buyers to explore listings more intuitively, uncovering insights that typically require multiple searches. “Now the site has come officially to life,” she asserted. “You are talking to our website and it is talking back.” For instance, users can ask why one property is more expensive than another, and the AI will provide a breakdown of the differentiators.
The home search process, described by Sponseller as a complex journey, is made easier with the new technology. “Your home is like a needle in a haystack that you’re trying to find,” she said, highlighting how the new search experience accommodates the unique nuances that matter most to buyers.
Ventura added that the use of conversational AI allows for dynamic adjustments to searches. “You could say, ‘Hey, Homes, bump it up by 50k,’ and all of a sudden the search changes,” he explained. Users can effortlessly modify their criteria, such as adding or removing features like pools or elevators while engaging in a back-and-forth dialogue with the platform.
Both executives were clear that the aim of the technology is to enhance rather than replace the role of real estate professionals. Ventura stated, “Our company name is CoStar, and we’ve always viewed the agent as the star. What we’re trying to do is deliver that well-educated, well-informed consumer to that agent so they can get more deals done faster.” Sponseller echoed this sentiment, noting that the technology streamlines processes for both buyers and agents, ultimately making agents more effective in serving their clients.
Looking ahead, the executives see considerable potential for integrating AI and property data into the home-search process. Sponseller expressed enthusiasm for equipping consumers with comprehensive data in an accessible manner. “It’s helping them make more informed decisions for potentially the biggest financial investment in their lifetime,” she noted. Ventura elaborated on the future possibilities, suggesting that deeper property insights could lead to predictive guidance for buyers, such as understanding projected long-term maintenance costs or the impact of renovations on property value. “It’s all about unlocking the proprietary data we have and feeding it to these models to get really good answers,” he said.
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