If there's one thing the all-powerful web has yet to conquer, it's recommendations. Be it music, news, or books, trying to find new content based on your tastes is an exercise in frustration (and, all too often, futility).
There are, of course, two diametrically opposed approaches to recommendations. On one end of the spectrum, there are algorithms which sift through your previous purchases, activity, friends' activity, etc., to find what you're most likely to love. On the other, there are good, old-fashioned human curators, laboriously poring through the mountains of content to bring you high quality, if not very personalized, recommendations.
Most companies fall somewhere in the middle of this sliding scale. Google Play Music, for example, relies heavily on algorithms to recommend music, but also employs human curators to feed the app's intelligence.
Music, though, is one thing: a lousy song only costs you about four minutes of your life. Books, on the other hand, require a considerable step up from music in terms of time invested. Ask any book lover about the headache that is finding a new book, and you'll likely need to pull up a chair- you're going to be awhile.
Amazon, arguably, leads the pack in terms of algorithm recommendations—mostly due to the unparalleled scope of its data—but it still falls well short of useful. Amazon realizes the problem, too, which is why it bought Goodreads, the industry-leading social networking site for book lovers. That aquisition has yet to pay dividends for users (presumably, it will, since Goodreads' forté is user recommendations and reviews).
The site is a simple tumblog which uses humans (and only humans) to recommend books. Each entry starts with a given book, then lists several books below it which are similar, along with the actual reasons they're similar.
For example, in the screenshot you'll see A Tale for the Time Being by Ruth Ozeki. If you've read and enjoyed it, GBY recommends you try Hey Nostradamus by Douglas Copeland. Why? Because it's also a philosophical coming-of-age tale. Or perhaps you'd prefer Kazuo Ishiguro's The Unconsoled for its "dreams melding with reality," much like A Tale.
Try getting that from an algorithm.
The only downside I see (and I'm nitpicking here) is only an issue for non-UK residents. The links to each book redirect to Waterstone or Foyles, both of which are UK-based, so U.S. customers will have to do a quick Google or Amazon search to find the books (or call your local bookstore). Otherwise, the site is a simple and elegant way to find your next read. And because it's a Tumblr, you can simply follow along. That adds a bit of serendipity to the process: by simply browsing through your Tumblr feed, you may come across a great book or two.
In a space that increasingly relies on algorithms for recommendations, Go Book Yourself is an oasis of literary humanity.