Navigating the Amazon Sales Ranking

In a previous post I discussed my book SELL YOUR BOOK ON AMAZON’s climb up the Amazon Sales Chart as a result of specific marketing tactics. I included the following graph, which we charted on the day of the campaign:

There are some interesting things to notice about this cart.  For instance, you will notice how rapidly the ranking climbs from 15,000 to 3,000.  And then, again, you will notice how quickly it climbs from 1000 to 200 (the difference in scale notwithstanding, of course).  But also notice how slowly it climbs from 50 to 29.  This is probably obvious, but I’ll say it anyway: The closer you get to a #1 ranking, the more books you need to sell. 

One section of my book discusses the Amazon Sales Rank in detail, and the information may be helpful when looking at the above chart, so I’ll include it below:

First, the disclaimers: Since the algorithm Amazon uses to generate its sales ranking is proprietary, the details contained herein are extrapolated from research and field tests. The resulting consensus finds Amazon’s system to provide marginal sales data at best.

To whit, read Amazon’s own definition of its system, slightly paraphrased from their FAQ: “The Sales Ranking system exhibits how books are selling. The lower the number, the higher the sales. The calculation is based on sales and is updated each hour to reflect recent and historical sales of every item sold. We hope you find the Sales Rank interesting!” This last sentence seems to indicate Amazon’s own perspective on the importance with which the sales rankings should be viewed.

You’re not supposed to find the sales rankings informative or helpful. You’re supposed to find them interesting.

In actuality, the process is somewhat more convoluted than they let on. The ranking does not depend solely upon the actual number of books sold, but rather, on a comparison against the sales figures of the other books in their database (all 5 million+ of them) within that same hour. Simultaneously, a trending calculation is applied to arrive at a sales trajectory. So, hypothetically, a book that held a ranking of 2,000 at 2pm and 3,000 at 3pm, might hold a 4,000 ranking at 4pm, even if it actually sold MORE books between 3-4 than it did between 2-3.

Current projections and historic sales information also play a key role in these calculations. In fact, the predictive nature of the Amazon ranking system is what makes it possible for a newly-released book to outrank an older established title, even though the actual sales figures for the latter far exceed the former.

That said, sales history takes a back seat to current sales rankings. Sales projections and trending take an active role here, which is why a book’s ranking can leap from 900,000 to 200,000 in the span of 24 hours or less. Does this mean the book has sold 700,000 copies in 24 hours? Absolutely not! What it does mean is that recent activity (i.e. purchases) for that book is trending higher than those 700,000 books it just surpassed. But, don’t get excited just yet; since the activity of those 700,000 other books range from slow to stagnant, one or two orders are sufficient to catapult a ranking.

If a book’s ranking breaks into the top 100,000, the sales history calculation starts to rear its head, which is why a “phenomenon” book has a hard time maintaining a high, legitimate ranking. A phenomenon is defined by a book that leaps from the high hundred-thousands into the lower thousands (or better) in the span of 24 hours or less, usually due to some concentrated marketing initiatives. Since Amazon’s sales history for that title doesn’t support the leap, the spike occurs and then quickly drops again.


Since the data is recalculated all the time, it’s impossible to arrive at accurate, cumulative sales figures, although those figures are applied to the algorithm during the calculation. No, to get a very rough idea of the actual number of books being sold, the sales ranking has to be dissected dynamically, with the same immediacy as the ranking being calculated. In other words, chart the ranking of the book at the same time every hour for 24 hours and then divide by 24 to arrive at its average daily ranking. Do that for seven straight days to arrive at its average weekly ranking.  You can do it all month long to arrive at its average monthly ranking. The longer your average timeframe, the more accurately your sales ranking will reflect “reality” (as opposed to a spike or dip in sales).