Jeff Seymour - Author of Fantasy, Literary Fiction, & c.: 2015

Mailing List

Friday, January 16, 2015

January is Bleak and Cold --- PUT EVERYTHING ON SALE!

Hey everybody! I'm proud to announce what I hope will become an annual tradition. Reaching deep down into my bag of poetical, lyrical language, I'm going to call it the BEAT WINTER Sale!

Basically, January sucks (although actually, it's beating the heck out of November and December this year). And what better way to fight the winter blues than by losing yourself in some free or $0.99 books? Over the next week and change, I'm putting my entire catalog on sale, so dig in and enjoy. There's no better time than now to share your favorite book with friends!

JEFF SEYMOUR'S FIRST ANNUAL BEAT WINTER SALE!

SOULWOVEN - FREE on Amazon.com and Amazon.co.uk 1/16 - 1/18 and 1/24 - 1/25













The first book in a dark epic fantasy series, SOULWOVEN follows two brothers and their friends as they try to stop the release of a dragon that will destroy the world. Called "artistic perfectionism" (Kirkus Reviews) and "a call back to the classic Epic Fantasy of Tolkien" (The Speculative Post), the book has over a million reads on Wattpad, and one of its key lines has been quoted thousands of times on Pinterest.

SOULWOVEN: EXILE - $0.99 on Amazon.com and Amazon.co.uk 1/23














The highly anticipated sequel to SOULWOVEN, SOULWOVEN: EXILE tracks the continuing travails of Litnig and Cole Jin. More and more is stripped from them as they strive to save their world from the dragon, and the darkness of existence asserts itself ever more deeply in their lives. Released on 12/12/14, the book was an immediate hit with reviewers, who said it "captures the horror and the brilliance of the human spirit" (So I Can Read!) and "builds excellently on the strong base it establishes in the first instalment" (The Speculative Post). It ranked #12 on The Speculative Post's Top 20 Books of 2014.

THREE DANCES - FREE on Amazon.com and Amazon.co.uk 1/16 - 1/18 and 1/24 - 1/25















A boy runs into the supernatural on his way to ask a girl to dance. A young woman wakes up hung over in a goddess’s bed. A mountain climber falls into a crevasse and hears the story of a glacier’s life. Jeff's debut short story collection, THREE DANCES explores gender, sexuality, youth, and oddness in the midst of beauty. See what came before SOULWOVEN, and why people liked Jeff's writing enough to fund his Kickstarter.

WHAT LIES IN DARKNESS - FREE on Amazon.com and Amazon.co.uk 1/16 - 1/18 and 1/24 - 1/25













Read Jeff's first foray into horror - a dark short story about a girl fighting off a supernatural being that takes over houses and eats the hearts of those who live inside. WHAT LIES IN DARKNESS was the result of the first All Hallow's Write event, and it's been a hit whenever Jeff reads it aloud ever since. Audio book coming soon!

Wednesday, January 7, 2015

Some Marketing Thoughts - Stars and Algorithms

Several months ago, I was e-mailed a link to a chapter from a technical book that explains how recommendation algorithms work. Because of the holidays and the Soulwoven: Exile launch, I only got around to reading it this afternoon, and I want to share some musings. As I was promised, it was interesting to think about how these algorithms are actually designed and how one, as an author, ought to try to take advantage of them.

The book in question can be found here, and the relevant chapter downloaded here.

In 9.1.1, it shows an example of what it calls a "utility" matrix. It posits some hypothetical user ratings for movies, then explains how an algorithm attempts to use them.

Notice that most user-movie pairs have blanks, meaning the user has not rated the movie. In practice, the matrix would be even sparser, with the typical user rating only a tiny fraction of all available movies. The goal of a recommendation system is to predict the blanks in the utility matrix.
I can't quote the matrix itself effectively here, but it's worth downloading the chapter to have a look at it. Basically, it shows that in a recommendation system (like Amazon's, BN's, etc.), you have a massive database of user-book rating pairs, almost all of which are blank. The recommendation system looks at what the user has rated favorably, then looks around for similar users and tries to see what they've also rated favorably (it probably also takes other factors, like genre, length, etc. into account as well).

Put pretty simply, that's where recommendations come from.

And that has driven home for me the importance of those star ratings in a new way. They're necessary for two things:

1.) They allow the algorithm to identify readers who haven't read your books but whose tastes are similar to those who have.

2.) They nudge the algorithm toward recommending other books by you to people who have given a high rating to one of your books in the past.

And that's on top of all the people-related reasons that star ratings matter.

Another salient quote:
In most applications, the recommendation system does not offer users a ranking of all items, but rather suggests a few that the user should value highly.
The way I read this, it helps explain in a new way why it's so important to connect with highly active readers. Let's say you have a reader who's read every bestselling fantasy novel that came out in the last year and rated it on Amazon. They also read yours. They like it enough to give it 5 stars. The algorithm can match a very high number of other readers to that reader ("Oh, this person liked Republic of Thieves and Soulwoven? Maybe all these other people who liked Republic of Thieves will like Soulwoven too). That doesn't work nearly as well if the readers who rate your book only read, say, three books a year.

 Final quote and thoughts:
An extreme example of how the long tail, together with a well designed recommendation system can influence events is the story told by Chris Anderson about a book called Touching the Void. This mountain-climbing book was not a big seller in its day, but many years after it was published, another book on the same topic, called Into Thin Air was published. Amazon’s recommendation system noticed a few people who bought both books, and started recommending Touching the Void to people who bought, or were considering, Into Thin Air. Had there been no on-line bookseller, Touching the Void might never have been seen by potential buyers, but in the on-line world, Touching the Void eventually became very popular in its own right, in fact, more so than Into Thin Air. 
I have spent a lot of time wondering what, exactly, happens when a book suddenly takes off on Amazon. It's a common enough story: "I spent three months or so seeing a few sales a week. Suddenly, in March, my sales took off. I have no idea why."

Maybe this is why.