Most advice on raising average order value is a list of tactics. We opened 42,570 orders from online stores to see what the basket actually looks like, and which levers the data really supports.
Average order value (AOV) is the average amount a customer pays per order: total revenue in a period, divided by the number of orders in that period. If a store took in fifty thousand from five hundred orders last month, its AOV was one hundred.
It matters because the customer is already paid for. The click that brought them cost the same whether they bought one item or three, and clicks are not getting cheaper: see what we measured for Google Ads and for Facebook and Instagram ads. A bigger basket is growth without buying another click: same media spend, same orders, more revenue, and a higher real ROAS.
Ask how to increase average order value and you usually get a list of tactics. We looked at the basket first. The data comes from online stores we grow, January to September 2026: 42,570 orders. Order value is what the customer actually paid, after discounts, including tax and shipping. Most of what follows is in percentages and multiples, which hold in any currency. Where an amount helps, it is shown in shekels with a dollar equivalent, at about 3.7 shekels to the dollar.
There is no universal good AOV. The average order value at the median store was ₪350 (about $95). The smallest basket was ₪160 (about $43), the largest ₪900 (about $243).
The gap reflects what each store sells and at what price, not how well it is run. A brand selling candles and a brand selling furniture will never share a benchmark. So a good average order value is not a number you find in an industry report. It is one that is high enough to pay for the click that brought the customer, the shipping you absorb and the margin you need, and one that is moving up over time. Compare your basket with your own, before a change and after it.
Across nine months, holidays and sale events included, the median index stayed between 95 and 103: a swing of a few percent, with no trend.
A single store can move more, but the conclusion holds: the basket does not grow by waiting. It takes a different offer. Five levers follow, each with what the data shows and what it cannot.
In every store we measured, the median order was lower than the average order, by 18% at the median store.
The median order is the one in the middle: half the orders are smaller, half larger. A few very large orders pull the average up, and the median barely notices them. So your typical customer spends less than your average order value suggests.
The typical customer spends less than the average order. Set the threshold by that customer, not by the average.
What the data shows: a threshold set from the average is aimed at a customer who spends more than most of your customers do. What it cannot show: where your own median sits. Your order export will tell you in a few minutes, and it is the first number you need.
At the median store, 46% of orders contained a single item: one product, one unit. Between stores that share ran from 3% to 85%.
When a second item goes in, the order does not double. An order with two units was worth 34% more than an order with one, at the median across stores. Three units or more: 2.06 times a single-unit order.
The likely reason: the second item is usually cheaper than the first, or it carries the discount. That is an explanation, not a measurement: we measured order value, not which item went in first.
What the data shows: a second item added between 16% and 70% in every store we measured, and close to half the orders at the median store still end with one item. What it cannot show: what happens if you offer a second item to everyone. People who buy two arrived with a different intention.
At the median store 51% of orders carried a discount, automatic or by code. Between stores: 8% to 88%.
In most stores, orders with a discount were larger than orders without one: by 10% at the median, measured after the discount came off. Not everywhere. At one end discounted orders were 34% larger, at the other 41% smaller.
What you can act on is the structure. A flat sitewide discount also goes to people who would have bought anyway. A tiered discount, where a larger basket earns a higher percentage, and a second-item offer both ask for something in return.
Then check that the margin survives. A discount on the second item gives up margin only on the added item. A discount on the whole basket gives it up on the first item too, which the customer was buying anyway.
In every store with enough orders of both kinds, orders with free shipping were larger than orders that paid for it: by 85% at the median, even with the fee counted inside the orders that paid.
That is not a lift caused by free shipping. Free shipping usually starts above a basket threshold, so large orders are the ones that get it. The threshold sorts orders. Whether it also moves them depends on where it sits relative to the typical order.
It can miss both ways. Too low, and most orders clear it anyway: at the median store 66% of orders paid nothing for shipping, through a threshold, a promotion or pickup. Too high, and one more item will not get the typical customer there.
Take a store that sits on our medians: an average order value of ₪350 (about $95) and a median order 18% below it, about ₪290 (about $78).
| What you set | Shekels | Dollars |
|---|---|---|
| Average order value | ₪350 | $95 |
| Median order18% below the average | ₪290 | $78 |
| Threshold from the averageAverage plus 20%. Typical customer adds 45% | ₪420 | $114 |
| Threshold from the medianMedian plus 15%. Typical customer adds 14% | ₪330 | $89 |
Set from the average, the threshold lands 45% above the typical order: the customer has to add about $35 (₪130), more than a second item adds at the median store. Most customers will not get there, and it will mostly reward people who were buying a lot anyway.
Set from the median, the distance is 14%, about $11 (₪40): less than a second item added in every store we measured. One more item, even a cheap one, clears it. The rule travels to any currency: find your median order, add a margin smaller than what a second item usually adds, and set the threshold there.
What the data cannot show: that moving the threshold will grow your basket. Treat it as a test, not a promise: compare the median order and the share of single-item orders before and after, and weigh the shipping you absorb against the margin on the added item.
A bundle turns several units into one decision: the customer chooses one product that already contains the second and third item.
What the data shows: an order with three units or more was worth 2.06 times a single-unit order. The order grows with the number of units, but every unit after the first is worth less than the first: two units were worth 1.34 times one. What it cannot show: anything about bundles alone. We did not separate them from ordinary multi-item orders.
Price a bundle like a second item: the discount on the set has to be smaller than the margin the extra units bring.
On Shopify, everything above is built in: automatic discounts with a minimum purchase, Buy X Get Y offers for the second item, free shipping above an order amount, and bundles. A good theme adds the cart progress bar and the complementary products block without an extra app; apps are only for what the store and theme do not already do. The tool is the easy part. The order matters more:
Average order value (AOV) is total revenue in a period divided by the number of orders in the same period. Decide what goes into the total, for example whether it includes tax, shipping and refunds, and stay consistent so this month compares with last month. In our data an order's value is what the customer actually paid, after discounts, with tax and shipping included.
There is no universal number, because AOV depends on what the store sells and at what price. In the stores we measured, the median store's average order value was ₪350, about $95, with a wide range between stores. A good AOV is one that covers your cost per order, shipping and margin, and that rises over time. Compare it with your own history, not with another category's benchmark.
Start with the second item. In our data a second unit added 34% to the order at the median store, while 46% of orders contained one item. Then move the free shipping threshold to just above your median order, use tiered or second-item discounts instead of sitewide ones, and offer bundles priced so the discount stays below the margin of the extra units. Test one change at a time.
Start from the median order, not the average order value, and set the threshold slightly above it, at a distance one more item can close. In our example, a store with a median order of about $78 would start at about $89, 14% above it. Then check that the shipping cost you absorb is smaller than the margin on the added item, and measure before and after.
Every growth playbook says the same thing: find your hero products and put everything behind them. We opened 31.5 thousand orders to see what heroes actually do. They carry the revenue, open the door to new customers and fill bigger baskets. They do not, on their own, bring customers back.
Daniel Hirsh8 October 202610 min readEcommerce is easy to define and harder to run. This guide covers what it means, how an order travels from the first click to the doorstep, the main types of ecommerce, what a business needs behind the store, and what 42.6 thousand real orders show about how online stores make and grow their revenue.
Daniel Hirsh8 October 20269 min readMost guides to building an online store start with picking a theme. We start with the data: 42.6 thousand orders in online stores we grow show where sales come from, when they arrive and who comes back. The build order follows from that: which pages first, how many products to launch with, what to set up on day one, and what it costs in money and time.
Daniel Hirsh8 October 202610 min readEvery Preneuriat client gets a live dashboard: store revenue, all media spend, real ROAS, updated all day. The first call goes both ways.
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