How to Increase Average Order Value in Ecommerce

To increase average order value, help customers buy suitable extras and test a free shipping threshold that your margins can support. Start with your store’s current order value. A bigger basket only helps when you keep enough of the sale after costs.

For a founder or ecommerce manager, the lowest-effort starting point is clearer product advice and one relevant add-on. A shipping threshold comes next if your platform already supports it. Bundles and volume offers take more work because you must manage stock and check the cost of each offer.

Before changing anything, collect order revenue and order counts for the same period. You also need product costs, delivery costs and your store’s conversion rate. Keep the traffic source and product mix comparable while you test one change.

Average Order Value Formula and Calculation

Average order value (AOV) is the average product revenue from each order over a chosen period. For a baseline before returns, the formula is product revenue after discounts divided by the number of orders.

Consider this hypothetical Australian store. It records $22,000 in product sales after discounts across 200 orders, excluding goods and services tax (GST) and shipping. Its average order value calculation is $22,000 / 200 = $110 AUD per order.

Use revenue excluding GST and shipping when you want to compare product spending and margins. Keep delivery charges separately, so a postage increase doesn’t look like customers buying more products. Use the same definition in both test groups.

For Shopify average order value, open Analytics, then Reports in the admin. Filter the category to Sales and open Average order value over time. Choose the reporting period and, for an online-store test, filter the sales channel consistently.

Shopify’s Help Center defines its AOV as gross product sales minus discounts, divided by orders. Tax and shipping are excluded. Discounts include line-item discounts and allocated order discounts. Post-order changes, including refunds, returns and exchanges, don’t reduce this AOV figure.

Shopify’s sales reports include pending, unpaid and cancelled orders, plus draft orders converted into orders. They exclude test and deleted orders. This is an order-placement measure, so track paid revenue and refunds separately when judging the cash you retain.

Average Order Value by Industry

Industry benchmarks depend on what the store sells and which stores a study measures. A replenishment product and a furniture purchase don’t need the same target.

Littledata’s 2026 order-value study measures 426 Shopify stores over a 90-day period. It converts purchase revenue into US dollars and calculates each store’s AOV. The page doesn’t define a geographic cohort, so these figures aren’t Australian benchmarks.

The table shows a median-to-top-quintile comparison band. Its upper figure is the threshold above which the top 20% of sampled stores sit. It isn’t a typical spending range for individual customers.

Category	Median AOV, USD	Top 20% above, USD	Stores sampled
Fashion and apparel	$102	$268	73
Home and furniture	$237	$954	57
Beauty and skincare	$68	$135	36
Health and supplements	$75	$101	35
Food and beverage	$81	$175	32

Benchmarks differ by region, study and revenue definition. A USD figure also needs currency conversion before you compare it with an AUD report. Use the table to understand category differences, then set a target from your own product prices and profitable order sizes.

Free Shipping Thresholds

Test a free shipping threshold about 20% to 30% above current order value as a starting hypothesis. This gives customers a reachable amount to add, but it doesn’t prove that delivery will pay for itself.

For a hypothetical $100 AUD baseline measured on the same basis as the threshold, the test range is $120 to $130 AUD. Start with $125 AUD if suitable products let customers cross it without buying something they don’t need. If your AOV excludes GST but your storefront threshold includes it, convert to the same basis before applying the percentage.

Check the economics before launching. Suppose an extra $25 AUD of product revenue generates $10 AUD after product costs, but free shipping adds $8 AUD of delivery cost. That leaves $2 AUD before extra packing and payment fees. These assumed figures exclude GST. Customers already above the threshold also receive free delivery, even when they add nothing.

1. Calculate the added delivery cost for newly eligible orders, including those that already qualify.
2. Show the threshold and remaining spend near the basket, using the same subtotal basis as checkout.
3. Split eligible traffic between the current offer and the new threshold if your tools support it.
4. Compare conversion and contribution per visitor before keeping the threshold.

If baskets get bigger but fewer customers finish checkout, inspect how much shoppers must add and whether delivery charges appear late. Lower the threshold or restore the original offer when the added contribution doesn’t cover lost orders.

Add-Ons, Bundles and Tiered Offers

Add-ons, bundles and volume offers increase order value by changing what customers buy together or how much they buy. Test them separately so you can see which change earns its cost.

An add-on is a suitable extra beside the main item, such as a compatible memory card with a camera. Compare its selling price with its product cost and any added delivery weight. The cross-selling guide covers how to choose useful pairings.

A bundle puts related items into one purchase, such as shampoo with conditioner. Check the combined product cost against what you retain from the bundle sale. A bigger order can leave less margin if customers would have bought both items at their usual prices. Use the guide to packaging products into bundles for bundle design.

A volume offer rewards a larger quantity, such as a lower unit price when a customer buys four pantry refills. The larger sale must cover the price reduction on every eligible unit. Include any extra fulfilment cost, and watch for customers shifting a future order into the current one.

Better Advice Leads to Bigger Baskets

Better advice gives shoppers a reason to add a suitable product: they understand how it fits their purchase and whether it is compatible. Clear specifications and answers to practical questions help customers decide whether an extra is useful.

For a hypothetical order-value example, a customer chooses a $120 AUD lamp and asks which bulb works with it. Advice based on the lamp’s socket and bulb limits identifies a suitable $15 AUD bulb. If the customer buys both, the product basket becomes $135 AUD, an increase of $15 AUD. These are assumed GST-inclusive shelf prices, before shipping, rather than a measured customer result.

A shopping assistant can suggest suitable extras when asked, provided its catalogue contains the compatibility details needed to answer. Give customers the reason the extra fits and let them keep the main item on its own. If the catalogue lacks a required measurement or specification, correct the product information before recommending a pairing.

For clothing, explain the garment’s measurements and the store’s sizing guidance. For electronics, identify the connector or supported model. Confidence about fit comes from useful product facts. A recommendation alone doesn’t establish compatibility.

Tracking Order Value Without Fooling Yourself

Track margin per order and conversion rate alongside AOV to see whether larger baskets improve the business. Use contribution per order after variable costs. Subtract product cost and fulfilment, along with payment fees and any delivery subsidy. Account for refunds and returns when enough time has passed for them to appear.

Conversion rate is completed orders divided by sessions on a consistent reporting basis. Contribution per visitor combines the margin retained on orders with how often visitors buy. It reveals a loss that a higher average order value can hide.

Consider a hypothetical test with 1,000 visits in each group. The original offer produces 30 orders at $100 AUD AOV and $30 AUD contribution per order. That is $3,000 AUD revenue and $900 AUD contribution.

The new offer produces 24 orders at $120 AUD AOV and $32 AUD contribution per order. Revenue is $2,880 AUD and contribution is $768 AUD. AOV rises 20%, yet conversion falls from 3% to 2.4% and total contribution falls $132 AUD. These assumed amounts exclude GST.

1. Record your baseline using one revenue definition and the same eligible traffic for each group.
2. Run one change and retain the original offer as the comparison where possible.
3. Check paid orders and retained contribution after refunds, with results split by traffic source when the mix changes.
4. Keep the change only when the contribution from comparable traffic improves and customers can still complete their purchase.

If AOV jumps after a handful of expensive orders, inspect order counts and the median order value before expanding the offer. If returns rise, inspect the products added and the advice shoppers received. Choose the first low-effort change you can measure, then use retained contribution to decide whether to continue.