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)

That's in the pipeline, yes.


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.

Audra wrote: "Denise wrote: "How and where do I find this?"
It's between groups and explore along the top."

I'll keep playing with it and see if I can get more results that look promising.

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.

Audra wrote: "Denise wrote: "How and where do I find this?"
It's between groups and explore along the top.""
your welcome

LOL TRAVIS! MY DH COMPLAINS BUT I'M READING AS FAST AS I CAN!








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?

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?




I really like this idea! I love to get interested in new books and authors.


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