A piece of software I use is "experimenting" with new pricing. They are completely changing how they price and thus the actual end price customers pay is up in the air.
There are a bunch of lessons and rants in how they did this experiment but what I want to write about is some copy they used. In it they claimed the average customer will pay 34% less with the new pricing.
(I can't quote the copy as it seems like they pulled their experiment last-night).
The 34% claim sounds great but the average customer is a problem.
When it comes to pricing changes, it doesn't matter what the average customer pays. It matters what the actual customer pays. What actually is charged to their credit card.
You might think if you pay $30 now so then you'll bill would drop to $20.
That's not how averages work though.
They could have someone paying $20 who now has to pay $104 and someone who is paying $25 who now has to pay $0. Those are actual bill estimates from myself and another customer.
Instead of only looking at averages, look at the maxes, ranges, distributions, and outliers. Taken all together they tell a much better story that just one number. It's more work but then you can spot problems like a 5x price increase to a customer.
Otherwise you might run into that Bill Gates statistics joke.
What's the fastest way to create the average millionaire?
Have Bill Gates walk into a room of people.
Looking at your average customer is great for following overall performance to see if your customer base as a whole are improving. That's what the Average Customer Analysis in Repeat Customer Insights is for. e.g. if your average customer's AOV is increasing then customers are spending more on average (some more, some less). Even then, the Average Customer Analysis should be just the first step to investigate your data.
I wouldn't use average customer stats for public marketing messages. It just takes one outlier to get upset and cause a lot of negative press.
Directive: Be careful using any "average" statistics, especially in public statements.
Eric Davis
Retain the best customers and leave the worst for your competitors to steal
If you're having problems with customers not coming back or defecting to competitors, Repeat Customer Insights might help uncover why that's happening.
Using its analyses you can figure out how to better target the good customers and let the bad ones go elsewhere.