Your Shopify store’s Average Order Value is very personal. It will be different than just about everyone else’s, even others in your industry. The more similar you are to your competitors, the closer it’ll become.
This personal performance of your Average Order Value means you have to use your own data to tell if you’re performing well.
It makes sense right?
You’ve probably already been doing it but perhaps not thinking of it as benchmarking:
- How’s my Average Order Value this year compared to last year?
- How is this cohort’s AOV versus that cohort?
- Are our winter sales depressing our AOV?
When you compare Average Order Value there are a few strong comparisons you should consider:
- Current year vs last year
- Year to year
- Current month vs last month (sometimes, see below)
- Current quarter vs the same quarter last year
- Any period vs your overall
That said, there are a couple of problem areas with AOV.
If your store has a sales cycle (e.g. busy in winter, slow in summer or the reverse), be careful comparing quarters. Especially if one quarter is your busy or slow season. Compare to the same quarter in a different year instead (e.g. 2023-Q1 vs 2022-Q1, not 2022-Q4).
Similarly, comparing the current and last months is useful but not if either month is part of your slow or busy season.
Comparing a period’s Average Order Value to your overall Average Order Value is really powerful and not that frequently used. This comparison lets you benchmark the period against your good and bad months (and downturn and boom times). While year-over-year is good to show constant growth rates, comparing to the overall shows lifetime improvements and progress.
What’s really cool is the Insights system in Repeat Customer Insights. It will automatically compare your Average Over Values in different periods and for different sales channels and then highlight your weaknesses.
These comparisons (and ones on other metrics) are included by default in the app for every account level.