This is a very useful information for a shop owner, since making someone buy another product with a higher value than his last purchase is a lot easier.
It is quite clear then that we have a better chance in improving the average order value if we try to make previous customers purchase in a higher value than trying to do the same with those who are not committed to our shop yet.
Nevertheless, identifying customers will low average order value isn’t quite easy and this kind of data do change constantly. Carrying out a single analysis won’t cut it but instead, we need to be continuous and consistent in communicating with different customers. If we were using manual reports, it would be an extremely time-consuming task and a very expensive one for an average shop owner.
But what can we do later identifying the customers’ key areas for improvement?
Our goal is to increase the average order value as well as the income of the shop.
We can create an export of our customers with low average order value, and use this in a marketing campaign aimed to increase their order value.