Zillow Implements AI to Improve the Online Home Search Experience
Powered by advanced natural language technology, homebuyers can enter longer, more detailed requests, just like they would on Google, to discover more accurate inventory matches.
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Zillow continues its march toward a better overall home buying experience with the advent of an improved way to find homes that match the preferences of different buyers.
With advanced natural language technology, homebuyers can enter longer, more detailed requests, just like they would on Google, to discover more accurate inventory matches. People can now find homes the same way they would describe what they want to friends and family, the company shared in a Jan. 26 announcement to Inman.
This means the app can interpret longer phrases, like “$700K houses in Charlotte with backyard” or “open house near me with four bedrooms.”
“This new tool is a game changer for home shopping because it helps shorten the sometimes long and stressful home search process by creating an easier and more modern way to search,” Jenny said. Arden, Zillow’s director of design, in the announcement. “And it delivers relevant search results in a simple and uncluttered way.”
It may also benefit agents who more accurately list desired features from their listings rather than simply rattling off the number of bedrooms and bathrooms, for example. As is common with online home searches, Zillow will allow users to save their search terms to receive alerts for new matches.
Zillow claims it’s the first iteration of this type of home search technology, but Localize, a New York City-based technology, implements a similar organic search methodology. The company raised $25 million in 2021.
To locate gathers “billions of data points” to provide information on hundreds of building and neighborhood attributes, including schools, future construction, weather conditions, proximity to popular stores, building violations, complaints, pests, natural light and high ceilings, among other aspects of properties and their communities.
The company also offers a hybrid human-AI concierge service called Hunter that serves as a home buying advisor, sending buyers curated, personalized listings on a daily basis that Localize then further adjusts based on user feedback on the results.
Regardless of who looked at natural language first or better, the advances present powerful benefits to the industry. Buying agents are constantly overwhelmed with the idea that they need to get new listings in front of clients before competing applications.
Truly, it is a battle that cannot be won and now, it doesn’t even need to be fought. The more information buyers have about listings, the easier it will be to serve and satisfy them.
“Zillow’s natural language search feature takes user queries and scans millions of listing details to bring relevant results to the surface. At the same time, the feature is training machine learning models to better respond to search queries that use natural, human-like sentences,” Zillow said.
Machine learning and enterprise automation are components of artificial intelligence. the theme was frequently bred this week at Inman Connect New York, in part due to the sudden increase in interest in ChatGPT, largely a natural language response mechanism, like those used in lead capture and tech support. ChatGPT can also be queried to provide written descriptions and therefore list content.
To date, Zillow’s Arden seems correct to comment that the future of real estate will be driven by the AI application of proptech.
“We are proud to be the first in the industry to offer this smarter way to search and excited to see how it learns and evolves to help every Zillow buyer find their perfect home.”
Email Craig Rowe