Many property search websites incorporate neighbourhood information, attached to property listings, but this flips it around – it allows consumers to find the neighbourhood first, then the home.
“With our expertise in data collection, standardization, and analysis, our clients were constantly asking us if we can help them with listings,” said Marc Siden, CEO of Onboard. “But we wanted to offer something to the industry beyond just the best, cleanest, and most efficient listings. So by combining our wealth of community, schools, and amenities dataset with the best listings data in the industry, then layering on a search logic that takes human preferences into account, we are able to offer the first search engine that works the way the human mind does.”
The Lifestyle Listings Engine was announced last week at the Inman Real Estate Connect Conference in New York, with details also published on the company’s blog.
It uses a Human Centered Search (HCS) API enabling a multivariate, multi-weighted search experience. Users are able to search based on schools system ratings, commute time, amenities, neighbourhood info, and more at the same time.
“For years, Onboard has been providing data analytics to companies such as CNN/Money for feature stories on selecting best places to live, best places for retirement, and best places for families,” said Peter Goldey, Chief Information Officer of Onboard. “We knew that our algorithms and our search logic were something that our clients in real estate could really benefit from, so we’ve created that toolset.”
The Lifestyle Listings Engine also features the most advanced handling of listings data, management of MLS relationships and IDX rules with its proprietary Compliancy Engine technology, and simplifies development by providing a single, consistent data feed from hundreds of disparate feeds.
According to Liam Dayan, Chief Technology Officer of Onboard, the HCS technology is made possible by the robust data handling technology behind the scenes: “What we’ve done is taken our expertise and systems for handling disparate data sources, aggregating them, cleaning them, and making the resulting data easy to use, and applied them to listings. We then blend that cleaned dataset with the rest of our content, using our proprietary system. That facility with data is the ‘secret sauce’ if you will that allows us to create applications like Human Centered Search.”
The Lifestyle Listings Engine is in final testing, and is slated for release to clients in mid-February.