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Posts Tagged ‘hunch’

Recommendation engine Hunch confirms that they’ve raised a new round of financing – $12 million – led by Khosla Ventures. Partner Gideon Yu, who joined Khosla Ventures last year, was previously the CFO of Facebook. He is now joining Hunch’s board of directors as part of the deal. Hunch was valued at $52 million in the round.

I spoke to cofounder Caterina Fake this evening about the round. Fake says that Hunch, which is less than a year old, now has lots of data to work with in making recommendations. In fact, she says, users have answered nearly 50 million questions on Hunch since launch, and the company can use that data to make better and better recommendations.

Wikipedia founder Jimmy Wales joined the company’s board of directors in late 2009.

Sometimes it takes a while for a site to find its legs. Hunch, which launched last March to much fanfare, is only now in the past few months capturing the attention of consumers. As the comScore chart above shows, Hunch recently hit a growth spurt, jumping from an estimated 130,000 unique U.S. visitors in August, 2009 to 371,000 in November, 2009. While the overall size of the audience is still small, nearly tripling it in three months certainly makes for an eye-catching chart.

Hunch takes a little getting used to. It is not a straightforward Q&A site. Co-founder Caterina Fake compares Hunch to a “Wikipedia for decisions.” Contributors create a series of questions aimed to help visitors make decisions. The more questions you answer about any given topic, the better guidance Hunch is supposed to be able to give you.

Like any crowdsourced service, it is designed to get better the more people use it. So far, people have answered more than 28 million questions to train the Hunch system about themselves. Although it is not necessary to do so to get suggested answers. But the more you put in, the more tailored the answers are to your specific needs. It took time to build a corpus of useful answers and decision trees which help people figure out everything from “What’s my favorite color?” to “What should I eat for lunch?” or “What places should I visit before I die?”

Early on, Hunch asked too much of its users before providing an answer, but now it seems to have enough topics and data to take users straight to its top recommendations. Shortening the cycle between landing on the site with a question and finding an answer may account for part of the jump in Hunch’s popularity. But Hunch is up against a lot of competition, including from social Q&A service Aardvark, which only recently expanded to the Web from an IM platform. My hunch is we’ll see both grow fast next year.

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Wikipedia founder Jimmy Wales is joining decision-making engine Hunch’s board of directors and will serve as an advisor to the startup. Hunch was recently launched by Flickr co-founder Caterina Fake as a platform to help users make decisions spanning a wide array of topics.

To help users make their decisions, Hunch presents them with a brief series of questions that have been submitted by other members, using their responses to help them make their ultimate decision. Wales joining the board makes sense considering that Hunch combines the crowd-sourced nature of Wikipedia with a Q&A site. On his blog, Wales wrote that Hunch.com’s “combination of community-sourced content and algorithmically-driven smarts is forging a promising path towards this potential future.”

Since Hunch’s launch in June, Hunch’s users have created more than 5,500 decisions, added more than 30,000 follow-up questions to those decisions, and contributed more than 50,000 decision outcomes. Users have answered more than 28 million THAY (”Teach Hunch About You”) questions and have ‘played’ more than 6 million decisions on Hunch

Fake, who worked on Yahoo Answers before leaving Yahoo, recently told us that “Yahoo Answers is not the answer,” saying that Hunch goes further than most Q&A sites with its algorithms and technology.

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Alicia Keys fans will have another reason to compulsively check her Facebook fan page today: Keys is releasing her new album The Element of Freedom exclusively through the world’s largest social network.  Fans will be able to tune in to her Facebook Fan page beginning today, where they’ll be able to stream the album free of charge (though they won’t be able to download digitial copies).  The album’s “real” release date isn’t until December 15.  This marks the first time a world-famous artist has debuted their album through the site.

Now, it isn’t unheard of for artists to debut albums and songs through the web, but this has long been an area dominated by MySpace.  MySpace still sees its share of exclusives, but in the last few months Facebook has been getting an increasing amount of attention from artists.  We’ve recently seen Chamillionaire and Sharkira release their new music videos exclusively though Ustream/Facebook, and there have been a number of big-name concerts streamed through the site as well.

The company powering the launch is called Involver, which has built out a strong selection of widgets and applications that brands can use to help engage users on Facebook.  Involver has powered the Facebook fan pages of over 20,000 companies, including big names like Nike, TIME, Microsoft, Guitar Center, and Snapple (you can see more of thekir clients here. The album stream is powered by a new Involver app called Music for Pages.

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When you want an answer to a question, you want it now, which is why the social Q&A service Aardvark first launched as an IM client, then via Facebook, then Twitter. Only today is it opening up its Website as a general social search engine. And it’s just a much better interface than the command-line-reminiscent prompts in the IM interface.

You still have to sign in or sign up for the service, which sends your question to people in your extended social network (usually on Facebook, but also Gmail or Hotmail contacts) who are also on Aardvark. In the IM client, this results in a somewhat annoying back-and-forth, interspersed with tips from Aardvark about what text commands to use to unleash more functionality (see bottom screenshot). On the new Website, you simply ask a question, and it goes out to find answers, which are then displayed in logical groupings.

For instance, I asked for suggestions for a good place to eat in near the Flatiron District in New York City, where my office is located. Within 11 minutes, I got three very good answers, including the ability to go back and forth to refine the answer. Richard R. (a friend of my former Fortune colleague David Kirkpatrick), asked how fancy I wanted the restaurant to be, and suggested 11 Madison, which is an excellent choice, but too fancy for a place to grab lunch with startup entrepreneurs. He then followed up with two other solid suggestions: Union Square Cafe (which is close, but not really in the Flatiron District) and Tamarind.

These are all good ideas, but I could have found them on Zagat’s as well. But three other people also gave me answers (all within 11 minutes). One suggested a nearby French Bistro I had forgotten about, but which is very good and cheap. Another pointed to a couple newer spots I have heard of but never tried out. And one came back with a restaurant that is just about to open called RYE. Now I feel like I’m in the know. Thanks Aardvark!

I tried this same question on rival Q&A site Hunch, but all I got back were results for places to eat and drink in Hell’s Kitchen. Wrong answer, too far.

I signed up for Aardvark a long time ago, and I’m constantly pestered with questions via IM which I simply don’t have time to answer (and I’m too lazy to change my settings). So I haven’t really been using it much. But with the Website, now I have a place to go when I have a question, and I’m definitely going to try it out some more. The downside of the Website is that you lose some of the real-time feel that you get through IM. You have to refresh the page to see new answers, for instance. It would be a simple fix, however, to stream the answers down the page as they appear. Currently, you just get an indicator of how many new answers are waiting for you.

I understand why Aardvark started out with IM and other methods before putting up fully-functioning Website. It had to build up users and a corpus of topics they can answer. When you sign up, you tell Aardvark what topics you are willing to be asked about, and Aardvark routes the questions appropriately. There are now more than one million topics Aardvark users can answer questions about and CEO Max Ventilla tells me that 90 percent of questions get answered within 5 minutes. And while he won’t say how many questions are being answered a day (it isn’t yet in the millions), he does volunteer, “We’re seeing days when we have one fifth the volume of Yahoo Answers.” Yahoo Answers attracts 15 million people a day (not all of whom ask questions).

Now people can go to the site and there is a built-in community of people who are ready to answer questions. You can either sign up (no more invites or Facebook login required), or just ask the Aardvark community at large without a sign-up. Unlike Yahoo Answers, previous answers are not searchable for everyone. The interactions remain semi-private, but they are also more immediate. With each new question, you’ll get an entirely new set of answers, depending on who within your social network responds.

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One of the most active sub-genres of search right now in terms of startup and new product activity is question and answer sites. Some searches are subjective and best answered by another human being. The success of Yahoo Answers proved this and spurred a raft of competitors to try their own hand at making Q&A better. These include Wiki Answers, Mahalo Answers, Aardvark, and Hunch. Now Ask, arguably the original Q&A search engine (in that it encouraged searches to be asked as a question, not that the answers came from other humans), is waving its arms to remind people that you can ask questions and find answers there as well.

In fact, it is doing a little more than that. Today, it launched a Q&A tab on its site which taps into a new database of 300 million pairs of questions and answers, which it has crawled and indexed from around the Web. In other words, it is crawling the other Q&A sites to look for the best answers to a particular question. It is also applying some semantic and clustering filters to group similar questions together and to try to surface the most relevant results. It is more of a search engine for Q&A sites than a Q&A site itself. You can’t answer any of the questions, just search for what other people have answered on other sites.

At first glance, I find it a bit unsatisfying. I asked it, What is the best Q&A site? Yahoo Answers seemed to be the consensus, but no other choices even surfaced. I tried, What is the newest Q&A site? and it turns up only a single result from someone on Yahoo Answers asking how to go about creating a new Q&A site.

Does Ask even search Mahalo Answers? If it did, it would have found this question (”What other question and answer services have you used, tried or have found interesting besides Mahalo Answers?”) that includes a long list of more than 25 Q&A sites, many of which I had never even heard of (including Afraid To Ask, Ask An Owner, Blurtit, and Quenchmark).

It is not just that the answers on the handful of queries I tried weren’t so great, it is that taking a purely algorithmic approach to Q&A is the wrong answer. Obviously there are way too many Q&A sits out there and Ask is trying to find the best existing answers from everything that is out there across different Q&A sites. But offering Q&A search without letting people ask new questions or improve the results by offering their own answers kind of misses the whole point of Q&A. It is people helping out people to find the best answers to their questions. At least the Q&A startups are trying to move the ball forward by building a community and incentives around Q&A (Mahalo Answers), machine-learning and game-play (Hunch), or let you tap into your direct social circle for more trustworthy answers (Aardvark).

These sites get smarter the more people who use them and some of them offer personalized answers as well. The right answer to any question often depends on who is asking. Ask thinks there is one or two right answers for everyone.

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In search, nobody wants to go up against Google. Even Microsoft is trying to position Bing as a “decision engine” even though it is really just a search engine. But Hunch, a startup which launched publicly today, is an actual decision engine. The only thing it attempts to do is help you make a decision through a question-and-answer interface.

Hunch is part of a recent flowering of Q&A sites (such as Aardvark and Mahalo Answers) which address a part of search that is orthogonal to what Google does. In part, these startups are responding to the success of Yahoo Answers, but they also push beyond what Yahoo Answers does. Flickr co-founder Caterina Fake, who worked on Yahoo Answers before she left Yahoo and is now running product design at Hunch, says: “Yahoo Answers is not the answer.”

The problem with Yahoo Answers is that most of the answers aren’t very good. As long as one answer is good, that is the one which comes up highest in results. But it doesn’t really learn from all the answers to a particular question come up with a better answer. Fake explains: “The question has been asked and answered thousands of times. Collective knowledge systems don’t work unless they retain knowledge, you can add knowledge to them in a simple and straightforward way, and it gets smarter every time somebody uses it.”

I had a long discussion with Fake about what Hunch is trying to do on Friday. You can search for questions which have already been entered into the system, or add your own. Each question is actually a series of questions with multiple-choice answers which take you down different paths (or, “decision trees’). The questions and answers are contributed by Hunch’s community (so far the site has been seeded by its 40,000 beta users). “Anyone can add a new set of sub-questions to main question, and improve the overall results in the same way that many people can contribute to the same Wikipedia article to make it better or add tags to someone else’s photos on Flickr. It only takes aminimal effort to make each question marginally better.

For instance, the question “Should I get a convertible?” leads to a series of other sub-questions aimed at helping you make that decision: “Are you okay with the possibility that you’ll pay more for a convertible?”; “How’s the weather in your city/country?”; “Do you live somewhere known for car theft or crime?”; “Do you keep a lot of things loosely scattered around the interior of your car?”; “”Do you often wear fancy or personally valuable hats or scarves?” After you answer all the questions, you get an answer. This could be a yes or no answer or s specific recommendation, such as what blogs you should read.

At the end of this process, you tell Hunch or not you agree with the result. Hunch not only has a results algorithm, but also has a question selection algorithm, which it tunes to each person. Theoretically, the more questions you answer on Hunch, the more it knows about you and the better follow-up questions it can present to come up with the best final answer. It sounds complicated, but the user interface is simple and game-like. You are presented with a series of questions, and you click on the answers which apply to you. Then at the end, you get an answer to the original question you were exploring.

Fake estimates that about 40 percent of the topics on Hunch right now are monetizable with ads or affiliate links. If you try to use Hunch to figure out which camera you should buy, for example, and the answer turns out to be the Nikon D80, already you will see a sponsored affiliate link to Amazon. Other business models might emerge in the future.

Other sites will be able to tap into Hunch’s question-selection and answer-selection algorithms to create their own Q&A system. Using Hunch’s API, a developer could create a custom product recommendation app for retail sites. Bob’s Bait And Tackle shop could set up a series of questions and answers to guide shoppers to the perfect fly or fishing tackle. All of these questions and answers would then feed back into Hunch’s core system. The more people who use the system, the smarter it should get.

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