As all agents, brokers, and home buyers know, searching for a home is a deeply personal process, and one of the most difficult challenges for buyers is narrowing down what they want. When a prospective buyer walks through a home or searches for one online, they are making hundreds of value judgments, often without ever consciously realizing them or expressing them to the real estate professional they are working with. Thankfully, artificial intelligence (AI) can now help bridge that gap and deliver a customized and personalized experience for consumers, without additional work by the agent or broker. For years, it has been easy to search for homes based on basic criteria like square footage, but what if a client wants something a little more specific, such as hardwood floors in all of the bedrooms, or homes with granite counters and white kitchen cabinets? That's where AI comes in.

Like many online retailers, Overstock closely tracks the behavior of visitors on its site. But transforming all those individual page views and clicks into actual revenue is easier said than done. The company recently discussed with Datanami how it overcame challenges in building its own one-to-one marketing analytics system, and what results it's delivered this year. Overstock emerged from the wreckage of the first dot-com boom with a winning business plan: sell the excess merchandise of failed retail outfits at below-wholesale levels, build a loyal following, rinse, and repeat. Now nearly two decades in, Overstock has expanded to sell new products, and it all adds up to nearly $2 billion in revenue annually.