Average order value

Average order value is what a typical order is worth: total revenue divided by the number of orders. It is the least discussed of the three numbers that multiply into store revenue, and in most small shops it is the one nobody has deliberately tried to move.

In short

• Revenue divided by orders, over a fixed period.
• The third lever on revenue, alongside traffic and conversion rate.
• Moving it costs nothing in advertising, which is what makes it cheap.
• It rises for bad reasons as well as good ones, so read it with order count.

Three levers, and this is the neglected one

Store revenue is traffic multiplied by conversion rate multiplied by average order value. Every one of the three multiplies the other two, which means a tenth added to any of them has the same effect on the total.

Most attention goes to the first. Traffic is visible, it has an obvious lever attached to it, and buying more of it feels like doing something. Conversion rate gets the next share of the attention. Average order value tends to get none. It is the only one of the three that can be moved without spending anything on advertising, and without waiting for a search engine to notice.

That is the argument for looking at it. A store that raises what a typical basket contains has raised the value of every visitor it already had, including the ones it paid for last month.

What actually moves it

The mechanisms are old and none of them are subtle.

• Bundles. Two things that are used together, sold together, at a price that makes the pairing obvious. This works because it removes a decision rather than because it discounts anything.
• A threshold. Free delivery above a certain order size, set a little above what people currently spend. The gap has to be small enough to be worth closing with one more item.
• Related items on the product page. Not a wall of everything, but the two or three things somebody buying this specific item usually needs.
• A larger size or a longer supply. Offering the option is often enough, because a proportion of buyers were always going to take it.
• Something added at the last step. A small item shown at checkout, chosen because it is an easy yes rather than because it is profitable.

None of these require new traffic, which is the point. They require somebody to look at what a typical order currently contains and ask what is obviously missing from it.

Where the number misleads

An average flattens a distribution, and store baskets are rarely distributed in a way that an average describes well.

One wholesale order in a month of retail orders will pull the figure up and leave you looking at a number that describes no real customer. The reverse happens during a clearance, when a run of single cheap items pulls it down and somebody concludes the strategy stopped working.

It also moves for reasons that have nothing to do with anything you did. Stock matters: when the expensive line sells out, the average falls, and it recovers when the line returns. Channel matters too, because customers arriving from a discount post and customers arriving from a search for the product itself do not buy the same way.

The habit worth building is to look at the median alongside the average when the shop platform will show it. When those two numbers diverge sharply, the average is being carried by a handful of orders. Any conclusion drawn from it is about those orders, not about the business.

Split it before you act on it

One number for the whole shop is a starting point and not much more.

Split it by channel first. Paid social, search and returning customers usually produce visibly different baskets, and knowing which channel brings the small orders changes what you would do about it. Split it by first order against repeat order next. A repeat customer buying more than a new one is the normal pattern, the absence of that pattern is worth understanding, and the split is the first step towards knowing your customer lifetime value.

Then look at how many items a typical order contains. If the answer is one, almost always one, the work is in what appears next to the thing somebody is already buying. If the answer is three or four, the basket is doing its job. The constraint is somewhere earlier, probably at checkout, or in whether people arrive ready to buy at all. Where cash on delivery is the common choice, the basket also has to survive a customer who has committed to nothing yet.