Bookshelves By Algorithm

Hillary Kelly is unsatisfied with literary suggestions from Amazon, GoodReads, or the latest newcomer, Bookish:

Bookish is hardly the first site to lure readers with the promise of perfectly calibrated recommendations (though it is unique in its employment of editors—real humans—who are empowered to supply recommendations as well, though its not clear in what capacity). Amazon, perhaps the gold standard in the industry because of its unparalleled data set, has long offered recommendations in the form of matching books that were “Frequently Bought Together” and the “Customers Who Bought This Item Also Bought” carousel. Assiduously tracking its customers’ habits, Amazon may know more about my purchasing patterns than my boyfriend does—and let’s keep it that way—but its recommendation engine has two crucial failings: Amazon does not know about books I buy or obtain in other capacities, and it assumes that I’m voracious for more from authors I’ve already purchased.

Jeva Lange is more positive:

Points to Bookish for their reader review section. The scoring system, which has so epically failed for Amazon, is designated into categories “readers,” “critics,” and “all” for ease of filtering out insane readers with vendettas or for focusing on the votes of those a little less highbrow than newspaper critics.

Chad W. Post doubts Bookish will catch on:

[W]hy would I stop buying from Amazon (if I don’t have huge moral issues), to go to Bookish? Why would I stop updating the GoodReads account I’ve been using for years to try and recreate it on Bookish? Remember Riffle? Remember Google+? They both faced similar issues, and neither really overcame it. What I don’t understand is why these companies don’t get that. Create something actually new and you’ll get what you want. Improve slightly on what people are already sort of, pretty much satisfied with, and they’ll ignore you.