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San Francisco start-up RentalRoost was recently featured in a CNNMoney article that took an in-depth look into the mission behind the lifestyle-based house and apartment finder, providing a glimpse into how the company is aiming to take the big data approach to a whole, new level.

The article, titled, “Can Facebook Tell You Where to Live?” went on to discuss how RentalRoost—and sister sites GrayRoost and Houserie—are aiming to take the guesswork out of the house-hunting equation.

Since launching in 2012, the trio of sites has been combining data from real estate listings, government records and social media sites such as Facebook, allowing RentalRoost users to search for properties and neighborhoods based on the criteria that are most important to them. Whether it’s having a big yard for the family pet or living in a central location that provides easy access to shops and restaurants, RentalRoost’s proprietary algorithms do the work behind the scenes to provide renters and buyers alike with lifestyle scores for specific neighborhoods.

The article, published on March 6, 2014, notes that RentalRoost is hoping to position itself as “the Google of real estate.”

Half of the sites 100,000 registered users sign into RentalRoost through their Facebook page, providing access to even more data that can be instrumental when it comes to recommending homes and neighborhoods that would best suit a consumer’s needs, including:

– Age
– Marital status
– Profession
– “Likes”
– Places you’ve “checked in”
– Census bureau data (incomes, poverty rates, unemployment)
– Transit options
– Schools
– Restaurants
– Art and culture

RentalRoost’s unique use of the treasure trove of data they have access to will provide a competitive edge, solidifying their place in the future of the industry by aiming to predict which neighborhoods will gentrify the fastest, providing buyers real data concerning where to invest. Agents will have a better idea of who to target when it comes to which houses will be up for sale and businesses will gain another way to target customers as data provides a first-hand glimpse into which houses will be more likely to order in or go out for a meal.

To see the article in its entirety, click here.