Hunch blogger widget

If you look at the right sidebar on this blog you’ll see a new Hunch widget.  It’s meant to be both fun and informative for the blogger and also the readers.

1. For the blogger, you can learn a lot of interesting things about your readership (for example, here are stats on readers). Soon, we’ll be adding more features for the blogger, such as inferred stats about your readers, derived by cross referencing their answers against our data set of 40M answers.

2. Blog readers get to learn about how they compare to other readers of the blog, and how readers of the blog compare to the larger population.  They can also play what we call the “prediction game” where Hunch tries to guess how you’d answer new questions you haven’t answered.  In our tests Hunch does a really good job.  It’s meant to be fun and also, frankly, a way for us to show off the power of Hunch’s predictive abilities.   If you want to try it, first answer 25 questions in the widget and then you’ll be be given the option to play the game or look at how you compare to other readers and Hunch users overall.

If you want to embed this widget on your own blog, go to (you’ll need to have a Hunch account and be logged in).

Any and all feedback welcome!

The challenge of creating a new category

One of the hardest things to do as a startup is to create a new category.  Bloggers and press have a natural tendency to “pigeonhole” – to group startups into cleanly delineated categories, and then do side-by-side comparisons, comment on the “horserace” between them, and so forth.

At my last startup, SiteAdvisor, we were at first consistently pigeonholed as an anti-phishing toolbar, even though what we did was help search engine users avoid spyware, spam, and scams, which (for various technical reasons) had almost no functional overlap with anti-phishing toolbars. My co-founder at Hunch, Caterina Fake, had a similar experience at Flickr.  Early on, people compared Flickr to existing photo sharing websites – Shutterfly, Ofoto, SnapFish – and found Flickr lacking in features around buying prints, sending greeting cards, etc.

Pigeonholing is one reason startups should actually welcome direct competitors.   It was only once a direct competitor to SiteAdvisor appeared that people started treating “web safety” as its own category (Walt Mossberg was the first one to legitimize the category with this article).

At my current startup, Hunch, being pigeonholed as a so-called Answers site is one of our main marketing challenges.  Hunch is a user-generated website similar to Wikipedia except, instead of creating encyclopedia entries, contributors create decision trees that help other users make choices and decisions.  For example, about 50 computer enthusiasts came together to create this decision tree about computer laptops that helps users with less expertise find the right laptop.  Hunch gets smarter over time as more people contribute to it.  So far, about 10,000 users have made 115,000 contributions to the site.  Last month, our third month after launch, over 600,000 unique visitors used those contributions to make decisions.

Many of the initial reviews of Hunch accurately reflected that Hunch is trying to create a new category of website.  Nevertheless, the tendency to pigeonhole Hunch as an Answers site remains. Answers sites allow users to ask a question and get back direct answers from other people.  There are many Answer sites including Yahoo Answers, Mahalo Answers, Vark, Answerbag, and ChaCha. These are all excellent and useful services – but have as much to do with Hunch as Ofoto had to do with Flickr.

There is no easy solution to avoid being pigeonholed.  All you can do is consistently, straightforwardly describe what you do, and then keep beating that drum over and over until the message gets through.

Which VC firm should I pitch?

A friend asked me the other day “Which VC firms should I pitch?” and I started to respond to him, but then realized that most of my knowledge of VC firms is already available online in the Which VC firm should I pitch? Hunch decision topic. That is the idea behind Hunch: to crowdsource the creation of decision trees, so that a group of knowledgeable people can get together and create a “virtual expert” that can be accessed by anyone.

Here is the VC chooser topic in embedded widget form (anything you create on Hunch can be embedded anywhere):

Which VC firm should I pitch? – make thousands more decisions on

Like everything on Hunch, this topic is completely user generated (“topic” is our word for what some people would call a “decision tree”). Users have full control over the questions it asks, the results (in this case VC firms), the descriptions, and a lot of more advanced functionality for “sculpting” the decision tree. If you go to the VC topic’s About page you can see that so far 7 people have contributed 86 firms and 5 questions to this topic (other topics have a much wider range of contributers, this one for example). The VC topic has been played (used by non contributors) 506 times, many of those users coming in via Google organic results for phrases related to pitching VC firms.

In addition, the results are all “trained” to be associated with responses to questions – meaning users have taught Hunch what to “believe” about each of the firms. For example, in red is what Hunch believes about Union Square Ventures:

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Users who find mistakes can just click and fix them, similar to how you fix things on Wikipedia.

So if you see anything missing or that you’d like to change, feel free to do so. I was one main people who worked on this particular topic so it is biased toward my tastes (e.g. Hunch’s own VCs – Bessemer and General Catalyst – rank extremely high).

If you don’t like Hunch’s Q&A process you can jump directly to the See All page, and then using the filters on the left to drill down.

If you are not logged into Hunch, the VC firms you see will be ranked by their popularity amongst all Hunch users. Hunch personalizes the rankings specifically for you if you create an account and answer what we call “Teach Hunch About You” questions. For example, when I am logged in and go to the Hunch page for Bessemer I see this on the right sidebar:
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Meaning that Hunch has learned to statistically correlate the questions I’ve answered about myself with liking Bessemer. At this point Hunch has statistically significant data (over 40M user feedbacks total) in most of our ~5000 topics so it usually works really well.