I have always been a book lover, but choosing what to read next can be difficult, especially after I finish an entertaining book. My first experience with a book recommendation platform was a result of a friend’s attempt to solve my dilemma. She signed me up for the website What Should I Read Next. A few years later, I came across another platform, Goodreads, but by then I was looking for a way to keep track of the books I had already read and to manage my ever-expanding “to-read” list. While I still receive recommendations from these platforms, I find them more useful as a way to manage my reading lists. But somehow I still wind up with enough books to read that it will take decades to finish them all.

Recommendation engines are used for products ranging from websites to books and are rapidly gaining popularity, in part because they help simplify decision-making.

These platforms use algorithms that take information you provide such as which books you have read and how much you enjoyed them and automate a list of books you may be interested in reading. This type of directed marketing has worked in the media and retail in the past and is proving just as effective for books.

Authors and publishers use these platforms as a more effective advertising strategy, so readers are less likely to see ads for books that don’t interest them. It also increases the chance that you will read the books you are recommended since the suggestions are catered to your tastes.  And the best part is that these websites are free to use!

But this kind of targeted recommendation also decreases your chances of finding something more unique. Like with the news, if you only get recommendations to specific content, you will likely only read that type of content. So while finding books is as easy as a few clicks, you can be easily bombarded with similar choices. Out of fifteen book suggestions, which ones do you read now and which do you save for later?

Unless you already have too many books on your “to-read” lists, these platforms can be great search tools. If you can’t stop adding books to your list, at least you know that you’ll likely enjoy reading them. These platforms try to automate your taste in books, so the more information you provide them, the more varied the recommendations will be.

Did You Know?

Book recommendation platforms can help make libraries and librarians more efficient than ever. Several libraries, including the New York Public Library, use Zola Book’s Bookish Recommends algorithm with more than 1.7 billion identifiers to provide suggestions with every library search. These platforms turn library book searches into database searches where keywords are as effective as titles.