What the number shows
Average order value, often shortened to AOV, is the typical amount a customer spends in one order. It is a simple ratio: total revenue divided by the number of orders over the same period.
It matters because it sits between traffic and profit. If you get the same number of orders but each is a little larger, revenue rises without paying for more visitors. Since fixed costs for each order, such as packing time, payment processing minimums and part of the shipping, do not scale one-for-one with order size, larger orders can also be more efficient to handle.
How to calculate it
Pick a period, such as a month. Add up the order revenue for that period and divide by the number of orders.
Here is a hypothetical example. Suppose a store had 80 orders in a month with total revenue of $4,000. The average order value is $4,000 / 80 = $50.
A few choices change the result, so decide them once and stay consistent:
- Before or after discounts? Using the amount customers actually paid is usually the most useful for planning.
- Include shipping and taxes or not? Many owners leave these out, because they are not income from products. What matters is using the same definition each time.
- Refunds. Decide whether you subtract returned orders. Looking at the figure both ways can be revealing if returns are common.
Mean versus median
AOV is an average, and averages can mislead. Imagine ten orders in a hypothetical week: nine of $30 and one of $330. The total is $600, so the mean is $60. Yet nine of the ten customers spent $30. The median, the middle value when orders are sorted, is $30.
If a few large orders pull the mean up, a decision based on it, such as setting a free shipping threshold at $60, would sit above what nearly everyone spends. Check the median too, and if your analytics tool allows it, look at a simple distribution: how many orders fall under $25, $25 to $50, and so on. It is one of the quick checks worth adding to your store analytics.
What moves AOV
Three things move it: the number of items per order, the price of each item, and the mix of products people choose. The goal is rarely to make shoppers spend more than they want to. It is to make it easy to find things they would reasonably want together.
Free shipping thresholds
Offering free shipping above a certain order value is a common nudge. A sensible starting point is a threshold somewhat above your current typical order. With a $50 average, a threshold of $60 gives a modest incentive to add one item. Set it too high and shoppers feel stuck; too low and it gives away shipping without changing behavior. Before committing, work out the real cost, as covered under free shipping, and confirm that the added margin on the larger order covers it.
Bundles and sets
Product bundles group items that belong together, such as a starter kit rather than separate parts. They can simplify choosing and make a larger purchase feel like a single decision. Make sure a bundle really saves the buyer effort or money, and that the pricing still leaves you a healthy profit margin.
Relevant suggestions
Showing “goes well with” items on product pages or in the cart can lift the number of items per order. Keep suggestions few and relevant. A small accessory that fits the item in the cart helps; a random unrelated product is clutter. The same idea works after purchase, in a confirmation email that suggests an actual companion product.
Quantity and volume options
For consumable products, a larger pack or a multi-buy price lets customers who already planned to reorder do so in one go. Be honest about the per-unit saving, and make sure the smaller option is still available.
Clear product information
Customers often add more when they feel sure about what they are getting. Good size charts, clear specifications and honest photos reduce hesitation, which can help both AOV and returns.
Nudging without pushing
There is a line between helpful and manipulative, and over the long run honesty is better for the business. Some practices to avoid:
- False urgency or fake scarcity, such as countdown timers that reset or “only 2 left” when that is untrue.
- Hidden add-ons, like pre-ticked boxes that add extras at checkout. Many places regulate this, and it generates complaints and refunds.
- Thresholds that trick people, for instance by raising shipping prices just before the line so the incentive looks bigger than it is.
- Pushing items that do not fit, which leads to returns, and returns erase the gain.
A good test is whether a customer, seeing exactly how the offer works, would feel it was fair. If you would be uncomfortable explaining it to them, skip it. Consumer rules on pricing and add-ons differ by place, so check what applies to you.
Watch the side effects
A higher AOV is only good if it does not cost you elsewhere. After any change, look at:
- Conversion rate. If a higher threshold or a busy cart page causes fewer people to finish buying, revenue may fall even as AOV rises.
- Return rate. Items bought on impulse or as poorly matched add-ons tend to come back more often.
- Margin per order. A discount that raises AOV but shrinks margin may leave you no better off. Use discount codes carefully.
- Repeat purchases. If customers feel pushed, they may not come back, which matters more than one larger order.
When you can, test a change on part of your traffic rather than rolling it out to everyone, using split testing. Small stores often have too few orders for a quick verdict, so be patient and look at several weeks.
A simple routine
- Calculate mean and median AOV for the last two or three months.
- Note your most common order sizes and how many items are in a typical order.
- Choose one change: a free-shipping threshold, one bundle or a relevant suggestion on your top product pages.
- Run it for a few weeks and compare AOV, conversion rate and returns against the earlier period.
- Keep it if the whole picture improved, revert it if not, and record the result.
Order value is one lever among several. A store that earns slightly larger orders from customers who are happy and return again is in a stronger position than one that squeezes every sale for the most it can get.