Announcing Goodreads Personalized Recommendations
Goodreads was founded with the mission to get people excited about reading. And the key to getting people excited about reading is to help them discover books that they’ll love, and then to enable them to share their thoughts and experiences with friends.
Today, Goodreads launches a new personalized book recommendation engine. It takes recommendations to a new level of sophistication by analyzing both books and, more importantly, the people who read them. It’s the Netflix of book recommendations.
Finding a great book recommendation online has been a hit-and-miss affair to date. We’ve all experienced the unhelpful suggestion to read another book by an author we already love. And how about the dreaded impact of buying gifts on Amazon only to have irrelevant book recommendations come up for months afterwards?
Earlier this year, Goodreads purchased a company that had built a very sophisticated book recommendation system. Today, after months of hard work, we’re ready to provide you with book recommendations that take into account what you like and don’t like and what certain books mean to you.
To get started, rate at least 20 books (and rate much more to get even better recommendations). Categorize your books in custom shelves that reflect what the books mean to you. Then explore your recommendations. We apologize for the impact this will have on the size of your to-read shelf.
How Goodreads Recommendations Work
The Goodreads Recommendation Engine combines multiple proprietary algorithms which analyze 20 billion data points to better predict which books people will want to read next. It maps out the connections between books by looking at how often they appear on the same bookshelves and whether they were enjoyed by the same people. On average, Goodreads members have 140 books on their shelves. With this information, the engine learns how your tastes are similar to or different from the tastes of other Goodreads members.
So, a big part of the secret sauce is…you, the Goodreads community. The Goodreads community is almost six million members strong, and you’ve added a combined total of 190 million books to your shelves!
Take best-seller The Help as an example: Goodreads members have added over 175,000 ratings of the book and over 40,000 reviews. In comparison, Amazon has, to date, less than 4,500 reviews and ratings.
But it doesn’t end with raw numbers. Goodreads members have put The Help on bookshelves called Historical Fiction, Friendship, Racism, Women’s Fiction and Cultural > African American. You can see how this book means different things to different people. If you’re approaching this as Historical Fiction and have enjoyed The Guernsey Literary and Potato Peel Society and A Tree Grows in Brooklyn, then a great recommendation for you is These Is My Words. With Amazon, the focus is on other best-sellers so someone buying The Help would get recommendations for books as diverse as Water For Elephants, The Hunger Games, and One Day.
We welcome you to try our recommendations on for size. Compare them with anything else you’ve relied on online. Then tell us (and your friends) what you think. We think you’ll be blown away, and that you’ll meet your next favorite book on Goodreads.
Today, Goodreads launches a new personalized book recommendation engine. It takes recommendations to a new level of sophistication by analyzing both books and, more importantly, the people who read them. It’s the Netflix of book recommendations.
Finding a great book recommendation online has been a hit-and-miss affair to date. We’ve all experienced the unhelpful suggestion to read another book by an author we already love. And how about the dreaded impact of buying gifts on Amazon only to have irrelevant book recommendations come up for months afterwards?
Earlier this year, Goodreads purchased a company that had built a very sophisticated book recommendation system. Today, after months of hard work, we’re ready to provide you with book recommendations that take into account what you like and don’t like and what certain books mean to you.
To get started, rate at least 20 books (and rate much more to get even better recommendations). Categorize your books in custom shelves that reflect what the books mean to you. Then explore your recommendations. We apologize for the impact this will have on the size of your to-read shelf.
How Goodreads Recommendations Work
The Goodreads Recommendation Engine combines multiple proprietary algorithms which analyze 20 billion data points to better predict which books people will want to read next. It maps out the connections between books by looking at how often they appear on the same bookshelves and whether they were enjoyed by the same people. On average, Goodreads members have 140 books on their shelves. With this information, the engine learns how your tastes are similar to or different from the tastes of other Goodreads members.
So, a big part of the secret sauce is…you, the Goodreads community. The Goodreads community is almost six million members strong, and you’ve added a combined total of 190 million books to your shelves!
Take best-seller The Help as an example: Goodreads members have added over 175,000 ratings of the book and over 40,000 reviews. In comparison, Amazon has, to date, less than 4,500 reviews and ratings.
But it doesn’t end with raw numbers. Goodreads members have put The Help on bookshelves called Historical Fiction, Friendship, Racism, Women’s Fiction and Cultural > African American. You can see how this book means different things to different people. If you’re approaching this as Historical Fiction and have enjoyed The Guernsey Literary and Potato Peel Society and A Tree Grows in Brooklyn, then a great recommendation for you is These Is My Words. With Amazon, the focus is on other best-sellers so someone buying The Help would get recommendations for books as diverse as Water For Elephants, The Hunger Games, and One Day.
We welcome you to try our recommendations on for size. Compare them with anything else you’ve relied on online. Then tell us (and your friends) what you think. We think you’ll be blown away, and that you’ll meet your next favorite book on Goodreads.
Comments Showing 51-100 of 261 (261 new)
Brad wrote: "Gotta agree with everyone else, this is a great idea. Will you be implementing the recommendations into the iPhone app too?"That's in the pipeline, yes.
I like this as a start. Most if not all, however, were books not on my list of to-read. How about run books on my to-read through the algorithm and tell me which of those I should read next.
Yeehaw, when I was finding a book site to track my reads, I sided with this one in the hopes that development for new features seemed likely here vs elsewhere. I was correct! Keep it up goodreads!!
Kara wrote: "Jeannette wrote: "QUESTION 1: I have been getting recommendations for stage adaptations of books by an author I love. I am not interested in the adaptations. What happens to other related works ..."
Thanks, Kara. I will edit my shelves. I was surprised to see recommendations for that shelf, as they are all books that I gave 1 or 2 star reviews.
Thanks, Kara. I will edit my shelves. I was surprised to see recommendations for that shelf, as they are all books that I gave 1 or 2 star reviews.
Thank you. I just found it.Audra wrote: "Denise wrote: "How and where do I find this?"
It's between groups and explore along the top."
I will be the sole dissenting voice--I'm a little disappointed. It seems to be making recommendations based on, at most, 3 of the books on the shelf (according to the little pop-up). So because I have *The Guernsey Literary...Soc", it recommends a gazillion WWII books, even though that's the only WWII book on my "historical fiction" shelf. It would be nice if it could do more aggregating based on reading patterns--most of the books on my Historical Fiction shelf are 19th-century, for instance, so I'd like more of those recommendations.I'll keep playing with it and see if I can get more results that look promising.
Brackman1066 wrote: "I will be the sole dissenting voice--I'm a little disappointed. It seems to be making recommendations based on, at most, 3 of the books on the shelf (according to the little pop-up). So because I h..."Just mark "not interested" on the titles you're not interested in and the algorithm will learn from that. The more books you rate and the more feedback you give the algorithm, the better your recommendations will get.
Denise wrote: "Thank you. I just found it.Audra wrote: "Denise wrote: "How and where do I find this?"
It's between groups and explore along the top.""
your welcome
I dislike receiving suggestions for boxed versions of series I have already read (ie The Complete Anne of Green Gables when I have read each individual title).
LOL TRAVIS! MY DH COMPLAINS BUT I'M READING AS FAST AS I CAN!
Love it! I found a few things that I didn't particularly care about and that was based off of just one book. But once I have more books to filter with I'm sure that will change. But I still added over 20 to my TBR list lol.
Just when I think I can't love this site anymore...you go and add this new feature!! Thanks so very much...I love it! It gives me a whole new trove to pick from whilst looking for new books! Also, thanks for always seeking ways to enhance the site. Fantastic work!!
I'm really impressed by this so far. Usually when I get online recommendations they're for either (1) books I already know about or (2) books I would never be interested in. But GR recs have already introduced me to a lot of new-to-me, great-looking stuff. It's a testament to both GoodReads and the GoodReads members!
Love it! Can't ever get enough books to read! Thanks for being my 2nd brain & keeping track & remembering all the books I love & want to read & have read!!! Love this site!!!!
Thanks! I've already bought a rec book for my Kindle. This is going to deplete my bank account even more...
I love the new recommending system. I'm definitely finding it helpful to find books that are not only similar to my interests, but also to what I've already read. Thank you guys so much. (And I'll forgive you for making my to-read list even larger :P)
How great! I love the new features you we come up with here! There is no other site on the web worth spending time on IMO. If my computer is one, GR is open... :)
Hey Guys,Nice going, and I mean that in a good way, not a bad way, though I was a little taken aback when I saw it at first, but then again, who says change can't be a good thing?
Hey Guys,Nice going, and I mean that in a good way, not a bad way, though I was a little taken aback when I saw it at first, but then again, who says change can't be a good thing?
Great idea. I haven't looked through all my recs yet, but they all seem to be very good. I'm not sure I should be looking at my recs, since I'm so far behind on all the series and books I want to read. Still, great idea and it looks very useful
How dare you make me add even more books to my TBR listing!!!! ;o) This is a great feature.....thanks for being responsive to the GR members and keep up the good work.
Great idea, but how does the algorithm handle indie-books, I wonder? I have several rated indies on my shelf, but it doesn't look like I get any recommendations for other indies unless I create a separate indie shelf and run the feature on that (and then those recommendations are all indies, all based on only one of the indie-books on my shelf, and in a variety of genres).
This took me to a whole new planet--just what I need--cannot wait to follow up on this one, thank you for a great service to us readers!
I really like this idea! I love to get interested in new books and authors.
I've been hoping for personalized recommendations like this!! I just started looking through mine last night, and my wishlist/to-read shelves are growing by leaps and bounds!
I love the idea but wish there was some way that recommended books I've previously read...maybe months or years ago...could be noted without it messing up my current shelf. I mean whats the point of loading it down with things I read so long ago. I don't want to be forced to wade through potentially hundreds of books to get to what's applicable now. I hope that makes sense.
























The algorithm does take into account the number of stars in your rating, as well as the shelves on which you placed the books.