Average Order Value is a metric that many stores like to boast about.
It's great to have a high average and you want to feel good about it, but comparing your average order value to another store's can be a waste of time.
Imagine if you will, three stores.
Jake's Jewelry, Sally's Soaps, and Mary's Machines.
Jake sells mid-range jewelry and has an average order value of $345.
Sally creates and sells handmade soaps with an average order value of $32.
Mary sells used construction vehicles with an average order value of $44,253.
If this was a contest of whose AOV was the largest, Mary would beat everyone else.
But that doesn't mean her business is better than Jake or Sally's.
What if it cost Mary $30,000 to acquire a vehicle, $5,000 in commissions and selling costs, and $2,000 to ship it?
(Unfortunately for Mary, USPS doesn't have a flat-rate box large enough for her.)
Mary is spending $37,000 in direct costs to make $44,253. Not bad, but what if she only sold one per month? Is the $7,253 net income enough for her business?
Look at Sally now. Her soaps cost $3 per order in supplies, $5 in labor, and another $5 in shipping.
She's paying $13 for every $32 order but is selling at a much higher volume at 1,000 orders per month. $19 net income per order becomes $19,000 for the month.
While these examples are extreme, they highlight why you can't compare Average Order Value between very different businesses.
You can look at your industry as a whole (jewelry, cosmetics, heavy equipment, etc.), you can look at close competitors, or you can look at yourself in the past.
But don't look at a specific store that is so different from yours.
There's too many differences to draw any conclusion without a bunch of more data.
In Repeat Customer Insights I calculate your Average Order Value along with a dozen other metrics. Seeing how the different metrics relate gives you a much clearer picture of how your store is doing than just your Average Order Value alone.
Eric Davis
Measure your customer loyalty
Measure the different levels of customer loyalty with Repeat Customer Insights. It uses various models to segment and grade your customers based on their behavior.