Book Sales Rank Estimator
Turn a Best Sellers Rank into a rough range of copies sold per day and per month. Enter one rank or many, and see how the estimate is made.
Paste ranks from product pages. Formats like "#45,000 in Books" and "Title, 45000" both work.
Royalty per month (optional)
You supply the numbers. Royalty rules differ by price, store and format, so check the publisher's own calculator.
Calibrate with a book you know (optional)
Scales the whole curve so it passes through your data point. One point can only rescale the curve, not change its shape.
Comparison
Swipe the table sideways to see every column.
Royalty figures ignore price-dependent royalty rates, returns, tax and currency conversion.
Rank against sales per day (both axes are logarithmic)
The shaded band is the margin of error. Dots are the ranks you entered.
The other way round: what rank means a given number of sales?
How these numbers are made
There is no official conversion, so this tool uses a curve built from the rank bands published inVappingo's KDP BSR sales estimator guide(a publishing-services site; the bands are approximate and the figures are for the whole Amazon books catalogue, which is weighted towards ebooks).
| Published rank band | Sales per day in the band | Point used on the curve |
|---|---|---|
| 500 to 2,000 | 80 to 300 | rank 1,000: about 155 a day |
| 10,000 to 50,000 | 3 to 20 | rank 22,400: about 7.7 a day |
| 50,000 to 150,000 | 1 to 3 | rank 86,600: about 1.7 a day |
- Each point is the geometric middle of its band. The curve joins the points with straight lines on a log-log scale, and continues the last slope for ranks beyond them.
- For paperbacks the ebook figure is multiplied by 0.35, the paperback factor used by the same source. This is one vendor's rule of thumb.
- The range shown is the estimate divided by two and multiplied by two. That factor is my judgement of how far such models can be off, not a measured error. Other calculators use private data and may differ a lot.
- The calibration box multiplies the whole curve by one number so it passes through a data point you know.
Worked examples (calculated by the same code as the tool)
The ebook rows at ranks 1,000, 22,400 and 86,600 are the points taken from the published bands, so they should match the "point used" column above. Paperback rows are those figures × 0.35.
Working on keywords for a book? Use the keyword packer. For percentages and margins, see thepercentage calculator. SwiftKit is not affiliated with Amazon.
Frequently Asked Questions
What is a Best Sellers Rank (BSR)?▼
It's the number shown in the 'Product details' section of a book's page on Amazon, such as 'Best Sellers Rank: #45,000 in Books'. A lower number means the book is selling better than most others right now. It is commonly reported to update about every hour and to reflect recent sales more than old ones, so it can swing a lot, especially for books that sell only a few copies a week.
Can a rank tell me exactly how many copies a book sells?▼
No. Amazon does not publish sales figures, so every rank-to-sales number you see online, including this one, is an estimate from a model. This tool shows a range, not a single figure, and the range is wide on purpose. Treat the answer as 'about this order of magnitude', not as a count.
Which rank should I enter?▼
Enter the overall rank (for example '#45,000 in Books'), not the smaller category ranks listed beneath it, such as '#12 in Puzzle Books'. Category ranks depend on how crowded each category is, so they don't convert to sales in a consistent way.
Why are paperbacks different from ebooks?▼
This tool estimates fewer copies per day for a paperback than for an ebook at the same rank. It does that by multiplying the ebook curve by 0.35, the figure used in the guide it draws on. That is one vendor's rule of thumb, and I could not check it against independent data, so use the calibration box if you have your own numbers.
Does this work for Amazon Australia, the UK or other stores?▼
The source of the curve does not say which Amazon store its figures are for, so treat the tool as a rough guide for the biggest store. Smaller stores very likely sell fewer copies at the same rank, but I don't have reliable data on how many fewer, so the tool does not guess. If you know your own sales in a smaller store, use the calibration box to scale the whole curve to match.
What does the calibration box do?▼
If you know that a book at one rank sells a certain number of copies a day (for example your own book at rank 80,000 sells 2 a day), enter both numbers. The tool scales the entire curve so it passes through your data point, which gives better estimates for other ranks than the generic model. It only has one data point to work with, so it can't fix the shape of the curve.
How is the royalty estimate calculated?▼
It multiplies your list price by the royalty rate you enter and subtracts the printing cost per copy (for paperbacks), then multiplies by the estimated copies sold in a month. You supply the three numbers, so check them against the publisher's own royalty calculator. It does not account for taxes, returns or currency conversion.
Why does the estimate become very uncertain for the top and bottom ranks?▼
At the top (below about rank 500) the rank changes hour by hour as large numbers of copies sell. The published rank bands the curve is built from stop at rank 150,000, so beyond that the curve is extended rather than measured, and the tool warns you. Above about rank 500,000 one sale can move the rank a long way, because the ranks are so crowded. In all these areas the figure is a guess.
Is my data sent anywhere?▼
No. The calculations run in your browser and nothing you type is uploaded or stored. SwiftKit is not affiliated with Amazon.