A “mean” profitable customer would be misleading. You could see that 99% of your customers lose money for you, while 1% earn all the profit (aka fat tail)
The point is you should be careful about reducing huge swaths of data to one datum. It often hides the more interesting insights.
> A “mean” profitable customer would be misleading.
In no place did I suggest "mean profitable customer" as a metric. I sort of said the opposite.
At the same time, in a traditional industry we wouldn't consider people with an evaluation license or sample or who came in to wander and see our wares a "customer". They're a lead and have a cost associated with them.
> The point is you should be careful about reducing huge swaths of data to one datum. It often hides the more interesting insights.
Sure. At the same time, if you dance with 30 numbers looking for insight, pretty soon you're practicing qualitative, wishy-washy innumeracy. The discussion is about KPIs, which are all about "reducing huge swaths of data to one datum" but also absolutely essential to run a real business day to day.
Monitor more than one, and keep your eyes open for where they go wrong, and be ready to change what you do.
The point is you should be careful about reducing huge swaths of data to one datum. It often hides the more interesting insights.