  We present a new method of estimating the distribution of sales rates of,
e.g., book titles at an online bookstore, from the time evolution of ranking
data found at websites of the store. The method is based on new mathematical
results on an infinite particle limit of the stochastic ranking process, and is
suitable for quantitative studies of the long tail structure of online retails.
We give an example of a fit to the actual data obtained from Amazon.co.jp,
which gives the Pareto slope parameter of the distribution of sales rates of
the book titles in the store.
