I have a number of series that would typically be described as normal skewed or Gamma distributed. For example, say I have a group of customers and have calculated their spend over a fixed length of time. I then create a histogram to see distribution of spend and find an extremely long tail for the small group of high-spenders. My question is, since I want to identify these high spenders, are there methods to empirically inspect a distribution of values and approximate the point at which the distribution becomes "long-tailed" to create a cut in the data? I am not looking at inspecting a histogram to find the long tail. Just looking for a consistent method to systematically cut the data.