The algorithm used by Amazon to rank its sales is patented, the details contained in it are extrapolated from research and field testing. The consensus results in a state that the Amazon system provides the best marginal sales data.
Amazon sales ranking system shows how products are sold. The smaller the number, the greater the turnover. Calculations are based on Amazon estimated monthly sales at Turbo Piranha.
Current estimates and historical sales information play a central role in this calculation. It is the predictive nature of Amazon's ranking system that allows newly uploaded products to overtake older and established titles, even though the actual sales for the latter far exceed the previous ones.
Image Source: Google
When the product rank exceeds, the sales history calculation starts to open, so that the product "phenomenon" is difficult to maintain a high legal ranking.
This phenomenon is defined by a product that jumps from hundreds of thousands to thousands (or better) for 24 hours or less, usually due to several focused marketing initiatives. Because Amazon's sales history does not support jumps for this title, jumps are displayed and then fall quickly.
How do you translate all these with current sales numbers?
The data is recalculated every hour and/or every day. It is not possible to get cumulative sales data, even though these numbers are applied to the algorithm during the calculation.