

Average revenue per customer is meaningless - soneca
http://data.heapanalytics.com/your-average-revenue-per-customer-is-meaningless
http:&#x2F;&#x2F;data.heapanalytics.com&#x2F;your-average-revenue-per-customer-is-meaningless&#x2F; Your average revenue per customer is meaningless
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balls187
It's not that ARPU is meaningless, it's just averages by themselves can be
easily misleading the same way percentages by themselves can be misleading.

> It turns out that for most businesses, revenue per customer follows a power
> law distribution.

It would have been better to provide a source for that statement, the way the
author provides data for Movies, Cities, and Web Traffic.

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bradleyland
Precisely. This piece seems like an over reaction to the discovery that
averages are a relatively blunt way of looking at data. They're not terribly
useful in a vacuum. Looking at a distribution (histogram) of your data is a
great way to understand the distribution of your data, but even then, you have
to be careful about how you bin your data.

This is good advice for data analysis in general. When looking at data, I like
to start with a histogram. Web server benchmarking is a great example.
Developers appear to have a strong desire to boil things down to a single
number.

"What's my endpoint response time?"

The answer is often an average, but the data is rarely well represented by
that number. Looking at a histogram reveals that.

