Best practices for getting your book discovered on Amazon

[Quantum]

Here's an article, which is backed up by excellent research, that describes some best practices for the metadata and marketing of your book based on the Amazon algorithms (basically procedures within Amazon's computer programs) that manage discoverability and search of books.

http://www.selfpublishingreview.com/2...

A9 is the company that Amazon uses for its search software.

"A9 Visual Search also powers solutions that lets customers search for products based on their visual attributes such as color, shape or even texture. Such solutions appear on Amazon.com and Zappos.com..."

although this article is worth not only a read, but a reread and continuous reference back to it, this bit of advice struck me and validates my own thinking--although with better evidence--in that you have to price within your (sub-)genre:

"What Amazon looks for is the number of sales for a product with the best profit in its category (Remember MAMM?). So if your book is 99 cents, but another book is selling at $2.99 but not as many as you, it’s likely Amazon will recognize the $2.99 book higher in rank because it makes Amazon more money. This means you need to do some research on what is selling in your potential category before choosing one, and also before choosing your price."

(Thanks to Gillian for posting post #3492 in the Goodreads Author Feedback group: https://www.goodreads.com/topic/show/...)

EDIT: Changed title and added description to get away from computer jargon, "algorithm". Also added to the Author resources spreadsheet.

[Nik]

Thanks, Alex. Helpful stuff, although I wouldn't overestimate the significance of understanding Amazon's algorithm ...

[Quantum]

Nik wrote: "Thanks, Alex. Helpful stuff, although I wouldn't overestimate the significance of understanding Amazon's algorithm ..."

true, but their machine learning tool--which i had been thinking about signing up for last year but had forgotten about it--is really cool:

"Amazon’s own Machine Learning tool (advanced) [get a 12-month free trial account] so that you can run your own parameters straight from Amazon’s data, “ML algorithms discover patterns in data and construct predictive models using these patterns. Then, you can use the models to make predictions on future data.”

another good point about reviews:

"Dave Chesson [Kindle ranking expert at SEMRush] says, 'If the Amazon search engine continues to place a particular product high in the SERPs based on just sales numbers, but customers aren’t leaving reviews or are leaving negative comments, Amazon will respond by lowering that product’s rankings and bring something else up further. While sales are important, Amazon cares about the customer experience as well.'

Not only that, since June 2015 Amazon’s overall star rating uses recency as a factor, so if you don’t spruce up reviews and sales, your book could start dropping in star value. Who wants 2 measly reviews next to their book listing? Not a lot of authors, is the answer."

[Justin]

Ahhh more algorithms!

[Michael]

Do whatever Marie Silk is doing...

I just got an email from Amazon highlighting Davenport House 2, 3 and 4!

The subject line of the email was "Davenport House 2: A New Chapter"

Congrats Marie !! Well done !

[Justin]

The problem with following Amazon's algorithms and using the system to help your own cause is that eventually it will change. Amazon knows this and will soon change their practices and algorithms to make sure they stay consistently at the top. As for us? We can continue to drag along and follow their path for as long as they stick to the one plan.

[Marie Silk]

Good to know, thanks Michael! I appreciate that they are pushing the sequels through email :). I seem to get about 100% purchase rate for the sequels after purchase of book 1 (not the same for free downloads), as well as KU pages for the sequels matching the first book, so maybe they get a little boost on the algorithm for that. All of my promotion efforts are for book 1.

[Eldon]

Excellent reading Alex! Thanks :)

[Graeme]

Congrats Marie.