AOV Calculator Calculator
Calculate Average Order Value, compare it across periods, and project the revenue impact of a target AOV lift — useful before you ship a free-shipping or upsell test.
AOV Calculator
A tool that computes Average Order Value from revenue and order count, with period comparison and lift projection.
Average Order Value (AOV) is total revenue divided by the number of orders over a given period. It is one of the three levers — traffic, conversion rate, AOV — that determine store revenue, and it's the lever most teams under-instrument relative to the other two.
This calculator returns your AOV for the period, the delta against a previous period, and the projected annual revenue uplift if you raise AOV by a target percentage. Use it to size experiments before you build them: a free-shipping threshold change, a cart upsell, a bundle, or a Klaviyo post-purchase flow.
AOV Calculator with lift projection
Revenue (current period)
$
Net revenue for the period — exclude tax, shipping income, and refunds.
Orders (current period)
Count of paid orders in the same period.
Revenue (previous period)
$
Orders (previous period)
Target AOV lift
%
The AOV uplift you want to size — e.g. 8% from a free-shipping threshold raise.
Current AOV
$80.00
Previous-period AOV
$75.00
Period-over-period change
6.7%
Projected annual revenue uplift at target lift
$467,200
Use net revenue (exclude tax, shipping income, refunds) for both periods so the delta reflects basket behaviour, not accounting noise. The annual uplift assumes the current period ≈ one month and order volume stays flat — if you're raising the threshold aggressively, model a conversion-rate downside separately.
Three things will keep the numbers honest. Use net revenue, not gross. Match the order count to the same revenue definition — if you exclude refunds from revenue, exclude refunded orders too. And pick periods of equal length and comparable seasonality; comparing Black Friday week to a normal November week will tell you nothing useful about your basket.
The formula behind the widget
AOV = Revenue / Orders
Revenue
Net revenue
Product revenue for the period, excluding tax, shipping income, and refunds.
Orders
Paid order count
Number of paid orders in the same period, on the same exclusion rules as revenue.
Shopify beauty store, last 30 days.
Net revenue: €480,000
Paid orders: 6,000
→ €80.00
Average basket of €80 — slightly above the typical beauty benchmark and a useful anchor when sizing a free-shipping threshold (the rule of thumb is to set it about 30% above current AOV).
AOV by itself is a vanity number. It moves up when you raise prices, change the discount mix, or sell more bundles — none of which necessarily mean a healthier store. Pair it with gross margin per order and conversion rate so you can spot the trade-offs.
What good looks like, by vertical
Typical AOV ranges by vertical for online stores in the €1M-€15M revenue band
| Vertical | Low | Median | High |
|---|---|---|---|
| Beauty & skincare | €35 | €55 | €85 |
| Apparel | €55 | €80 | €130 |
| Home & decor | €60 | €95 | €180 |
| Consumer electronics | €90 | €160 | €320 |
| Supplements & wellness | €40 | €65 | €110 |
| Pet | €35 | €55 | €80 |
Where you sit in the band matters more than the absolute number. A beauty store at €55 AOV is mid-pack; the same store at €85 is at the top end and likely running effective bundles or subscription. If you're below the low end, your single-SKU rate is probably high — that's a bundling and cross-sell problem, not a pricing problem.
Three experiments that move AOV
Free-shipping threshold. Set the threshold roughly 30% above current AOV — at €80 AOV, try €99 or €105. Watch conversion rate alongside AOV: a threshold that's too aggressive lifts basket size on the orders that complete, but kills the orders that don't. Measure revenue per visitor as the tiebreaker.
Cart upsells and bundles. A relevant complement (sock to a shoe, conditioner to a shampoo) typically lifts AOV by 4-9% with no conversion impact. Irrelevant suggestions do nothing. Use real co-purchase data, not what the merchandiser thinks pairs well.
Tiered discounts. "Spend €X, save Y" beats a flat percentage off because it forces basket-building. The mechanic is fragile though — readers anchor to the discount, not the products, so it can train customers to wait for promos. Run it as a time-bounded test, not an always-on default.
Mean AOV hides the distribution
One €4,000 wholesale order on a normal Tuesday will lift your monthly mean AOV by several euros and tell you nothing about typical shopper behaviour. Look at the median order value alongside the mean, and segment by acquisition channel — paid social baskets often run 20-30% below organic baskets and need separate targets.
AOV calculator FAQ
No. Use net product revenue — exclude tax, exclude shipping income, and net out refunds. Including shipping makes the number drift whenever you change your shipping policy, which defeats the purpose of tracking basket behaviour.
They're used interchangeably in most contexts. Strictly, basket size sometimes refers to units per order rather than revenue per order — check which definition your analytics tool uses before benchmarking against external numbers.
The safest levers are relevant cart upsells and bundles using real co-purchase data — they typically add 4-9% to AOV with negligible conversion impact. Free-shipping threshold raises work too, but always measure revenue per visitor, not just AOV, because aggressive thresholds suppress completed orders.
GA4 only counts sessions where the purchase event fired correctly, and it usually includes tax and shipping by default. Shopify reports on actual paid orders with its own revenue definition. Pick one source of truth — usually Shopify — and use GA4 for segmentation, not absolute revenue.
Weekly for trend monitoring, monthly for reporting, and per-test for experiments. Avoid daily AOV charts — daily variance from one large order is high enough to mislead you, and you'll start chasing noise.
Yes. Paid social typically delivers a basket 20-30% smaller than organic search or email, because the shopper intent is different. A single blended AOV target will under-serve your email cohort and over-stretch your paid social cohort.
A well-designed free-shipping threshold change or upsell module typically delivers 3-8% on AOV. Anything claiming a 20%+ AOV lift is usually a pricing change in disguise or a segmentation artefact — verify by checking conversion rate moved in the opposite direction.
No. If a free-shipping threshold lifts AOV by 10% but drops conversion rate by 12%, revenue per visitor falls. Always evaluate AOV changes alongside conversion rate; revenue per visitor is the integrated metric that tells you whether the change is a real win.
AOV is one input to LTV: lifetime value ≈ AOV × purchase frequency × gross margin × customer lifespan. Lifting AOV through bundles often raises LTV proportionally; lifting it through one-off discounts on bigger baskets can actually compress repeat-purchase rate, so the LTV impact is smaller than the AOV impact suggests.
Below ~200 orders in the period, a single high-ticket outlier swings the mean significantly. Either lengthen the window until you clear that threshold, switch to median order value, or exclude outliers above the 99th percentile before averaging.
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