Average Order Value (AOV) gets mentioned often in ecommerce metrics.
Since it's just a single value, the strategies around improving it are pretty basic though. Often it's just "increase AOV by ..." with hundreds of tactics listed.
You can build a different strategy with it though. One that's more adaptable and effective.
Instead of looking at the value itself, look at each customers' relationship with AOV.
One relationship would be customers who consistently spend more than the Average Order Value. These customers are showing behavior you want to encourage and could be large-scale buyers or fans of your products.
Thinking about large buyers alone, whole new strategies and tactics open up for you to find ways to connect with them. Then fans have another set of strategies.
Those strategies might fall into different tactics like loyalty programs and events for fans versus bulk discounting or industrial-sized bags for large-scale buyers. Each tactic could then be tested to see how the customer behavior changes and how AOV as a whole changes.
That's just for the "above the AOV" group. There are two other large segments for "below the AOV" and "close to the AOV". Inside those are plenty of other groups of customers who might respond to different tactics.
This is why the Customer Grid in Repeat Customer Insights breaks this down into five different segments (and 25 different RFM scores). You have a lot of power if you go one step beyond the basic AOV metric and apply it to actual customers.