A New York-based startup company called Hunch has been brought out by Silicon Valley's eBay for its ability to recommend items and/or services based on user data.
The online marketplace known as eBay has brought out a New York-based "recommendation service" called Hunch.
"What do you do when you need a recommendation?" asks a video on the Hunch website. "You probably reach out to someone who knows you. Someone who gets you. Someone who has a good sense of what you like and who you are."
This "someone" as the video goes on to explain, is more than likely a friend who knows you almost as well as you know yourself. Hunch, as a service, makes the claim that it is essentially a digital incarnation of that friend.
With recommendation utilities for just about anything you can buy or enjoy, Hunch has users fill out a "fun" survey and link the said service's account to those of Facebook and/or Twitter. This in turn tells it a person's interests as well as connects them to like-minded people who share their tastes.
As eBay's press release states: "Hunch’s technology talent and its deep expertise in areas like machine learning, data mining and predictive modeling are expected to help eBay expand and grow merchandising and relevance capabilities to further improve the shopping and selling experience for eBay customers."
Marketplace users are expected to benefit from this service by coming across unpredictable, albeit significant recommendations based off of their particular interests and tastes.
“We are engaging consumers in innovative ways and attracting top technologists to shape the future of commerce,” said eBay Chief Technical Officer, Marc Carges. “With Hunch, we’re adding new capabilities to personalizing the shopping experience on eBay to the individual relevant tastes and interests of our customers. We expect Hunch’s technologies to benefit eBay shoppers as they browse and buy, and to bring sellers on eBay new ways to connect the right products with the right customers.”
Hunch, as a company, got its start in 2009 utilizing a practice known as machine learning, which analyzes sets of developing algorithms allowing computers to "learn" new behaviors based on empirical data. In the case of eBay recommendations, the company takes information regarding users' preferences and creates a "taste graph" which in turn connects consumers to every item or service they hold dear.
"The technology is almost an uncannily good fit for the eBay recommendation problem," said Hunch co-founder, Chris Dixon.
Hunch's technology is highly adaptable according to Carges and Dixon, and as such might allow them to implement it into other parts of eBay like the site's search engine. Carges added that said technology could also be utilized in some of eBay's other properties such as StubHub.
As a result of this buyout, all of Hunch's employees will be inducted into eBay's Search and Buyer Experience team. Hunch headquarters will stay in New York City, which Carges told MercuryNews.com "was a good selling point because it gives eBay a presence in Manhattan's growing tech sector."