We’re all familiar with Amazon’s sales rank, those tantalizing numbers that have driven authors to obsessively revisit their pages over and over in hopes of seeing their book climb through the ranks.
Yet, as a closely guarded secret, Amazon’s sales rank remains a perpetual source of confusion and myth.
“Why did my sales rank go down when I sold more books this week?”
“Why did my sales rank go up when I didn’t sell anything?!”
“How did the sales rank of this book leapfrog over mine when I’ve sold ten times as many books?”
Amazon won’t disclose their proprietary algorithms, but thanks to some clever analysis by indie authors, that formula has been reverse engineered. And once you understand that formula, the quirks of sales rank make much more sense, and you can use them to your advantage.
Amazon’s sales rank algorithm is surprisingly simple…
1. Each sale or download of a product counts as one point toward a hypothetical “rank score”.
2. Each day, the preceding day’s score decreases by half, and is added to today’s points.
3. For each category on Amazon, books are ranked based on their current scores.
Monday, a book sells 32 copies. That’s 32 points towards its ranking.
Tuesday, the book sells 36 copies. Those 36 points are added to half of Monday’s total (32 / 2 = 16 points), for a total of 52 points.
Wednesday, the book sells 16 copies. Those 16 points are added to half of Tuesday’s total (52 / 2 = 26 points), for a total of 42 points.
…but the devil is in the details.
The underlying process is simple, but there are aspects of the process that contribute to the “strange” behavior of the algorithm.
Sales rank is relative to other books.
A book does not exist in a vacuum. As your book rises in sales rank, it will displace other books. As other books rise through the ranks, your book may be pushed downwards.
This counterintuitive feature of the algorithm is responsible for more confusion than any other.
The more recent the sale, the more weight it has.
Because the formula weights sales by recency, the effect of a sales spike quickly fades. The algorithm favors steady sales over a dramatic surge.
Consider the two books below (Figure 1). Book A experiences slow, constant growth for the first two weeks. Book B offers a promotion which results in an explosion of sales, but those sales quickly settle back to normal levels once the promotion ends.
At the end of the second week, Book A holds a higher sales rank — and has better visibility — even though Book B sold over three times as many copies.
In the long run, steady, organic growth outperforms sudden bursts of activity.
And this underscores a point we’ve made in the past: publishing success is a marathon, not a sprint, so authors should be focused on long-term success.
Reviews, ratings, and price do not affect sales rank.
Sales rank is governed by sales and downloads, with a little adjustment by Amazon’s algorithms. Sales rank is unaffected by the number of reviews, ratings, or any aspect of a book other than its sales performance.
Enrollment in KDP Select/Kindle Unlimited does not confer any direct advantage to sales rank.
Titles in KDP Select do not receive higher placement just for enrolling in the program. However, downloads of books through Kindle Unlimited and Kindle Online Lending Library are treated as sales, and they are credited immediately.
A download is immediately recorded as a sale in the sales rank algorithm, regardless of what percentage of the book is read.
High sales rank does not guarantee high placement in search results.
Sales rank plays a very minor role in determining the order of Amazon search results. Other factors such as relevance, keywords, sales history, product listing quality, and available inventory may influence Amazon’s algorithms. Therefore, a book with high sales rank may appear later in search results than lower-ranked books.
It takes twice as many sales to hit a rank than it does to maintain it.
Because each day’s sales rank builds on previous sales, twice as many sales are needed to initially achieve a rank as compared to maintaining that rank. In other words, an author may need 40 sales to initially hit a given rank, but once that momentum is established, they will only need 20 sales per day to maintain that score. (Sales rank may still fluctuate due to the performance of other titles around it.)
Similarly, if no sales are made, the book’s score is cut in half on the following day.
Twice as many sales are needed to hit a rank initially; each day without sales halves a book’s score.
Pre-orders are counted immediately.
Pre-orders are counted on the day the book is ordered, rather than on the date of the book’s release. This explains how books that have not yet been released may have a high sales rank, a common source of confusion.
Sales momentum is a key factor in the algorithm. The early boost from pre-orders have the potential to propel a title onto the Amazon charts faster and for a longer period of time than a launch day blitz alone would.
Taming the Algorithm
Now that we understand how the system works, we can leverage it.
- Sales rank is relative, and changes in rank may be due to the performance of other books
- Higher sales rank does not mean higher overalls sales
- It takes half as many sales to sustain a rank as it does to initially hit it
- A launch day blitz may briefly attain a high sales rank, but steady, organic growth will sustain it
- Pre-orders increase visiblity and jump-start your book’s sales rank
- Kindle Unlimited downloads immediately affect your sales rank, regardless of whether they are read
Remember that sales rank changes daily: it’s never too late to hit the Best Sellers list!
In addition to my own experiments, this article draws heavily on the work of German indie author Matthias Matting of Die Self-Publisher-Bibel, as well as Author Earnings’ excellent analysis which confirms Matting’s findings on a much larger scale. (The AE presentation by Data Guy is well worth exploring.)
Their outstanding contributions to the author community are gratefully acknowledged.
OVER TO YOU
Do you have questions about Amazon’s sales rank? Post your comments below!
Wondering how to make the most of online retailers? Don’t miss these useful posts from our archive.
- Understanding Amazon’s Recommendation Engine — by David Gaughran
- How to Reach Readers in the Age of the Algorithm — by Jane Friedman
- How to Reach More Readers by Harnessing Retailers’ Algorithms — by Simon Denman