What Is a Good Average Order Value for a Shopify Store? (2026 Benchmarks)
Average order value (AOV) is total revenue divided by number of orders, and a good AOV for a Shopify store is one that is higher than your own trailing 30 days, because AOV is a function of your price points and catalog far more than of any industry standard. Published cross-industry figures generally place typical ecommerce AOV somewhere in the 50 to 150 USD band, with fashion and beauty toward the lower half and furniture, electronics, and B2B far above it, but comparing your number to another category's benchmark tells you almost nothing actionable.
I watch AOV data across thousands of stores through our upsell tooling, and the pattern is consistent: the useful benchmark is always the store's own baseline, and the useful question is which mechanics move it.
TLDR: Key Takeaways
- AOV = total revenue divided by total orders, over a defined period. Shopify Analytics reports it directly.
- Category dominates the number: a 35 USD AOV can be excellent for accessories and alarming for furniture. Benchmark against your own trailing 30 days, not the internet.
- Track margin per order next to AOV; an AOV lift bought with deep discounts can shrink profit.
- The 3 fastest movers: quantity breaks on consumables, a free shipping threshold set 15 to 25 percent above current AOV, and 1 cart offer at the add to cart moment.
How Do You Calculate Average Order Value?
Divide revenue by order count for the same period. A store with 24,000 EUR in revenue from 480 orders in June has a June AOV of 50 EUR. In Shopify, open Analytics and the Average order value report gives the figure directly, with date comparisons. Two hygiene points: measure a consistent window (trailing 30 days works), and decide once whether your figure includes shipping and taxes, then never mix definitions between comparisons.
What Is a Good AOV by Store Type?
Directionally, from published cross-industry reporting and what I see across merchant data:
| Store type | Typical AOV band (USD) | Why |
|---|---|---|
| Accessories, beauty, consumables | 25 to 60 | Low unit prices, offset by repeat purchase |
| Fashion and apparel | 60 to 120 | Mid unit prices, multi-item carts common |
| Home, electronics | 100 to 250 plus | High unit prices, single-item orders common |
| Furniture, B2B, wholesale | 250 plus | Big-ticket or bulk by nature |
Treat these as orientation, not targets. A consumables store at 40 USD AOV with a 60 percent repeat rate is a better business than a furniture store at 400 USD with razor margins and no repeat purchases. Which is the second point: AOV is 1 input to revenue per customer, not the scoreboard by itself.
Why Do AOV Benchmarks Mislead?
Three reasons. Mix effects: the same store's AOV swings with its traffic mix, since sale-period and discount-code traffic buys smaller. Definition drift: sources differ on whether shipping, taxes, and refunds are included, so cross-source comparisons wobble by 10 to 20 percent on definitions alone. And survivorship: published benchmarks over-represent large stores. The comparison that survives all 3 problems is you versus you, 30 days ago, with seasonality noted.
How Do You Raise Your AOV From Wherever It Is?
The mechanics are the same at every starting point; only the offer content changes. The 3 fastest movers, each under 30 minutes to set up: quantity break tiers on anything customers use up, a free shipping threshold set 15 to 25 percent above current AOV with a progress bar, and a single cart popup offer firing on add to cart with a complement at 25 to 50 percent of the main item's price. Then frequently bought together on bestsellers and a post-purchase 1-click offer as the second wave. All the offer mechanics above run from Libautech Bundles & Upsell (Built for Shopify, 7-day trial); the full playbook is in our guide to increasing average order value.
Measure weekly against the pre-change baseline, and hold margin per order next to AOV so a discount-fueled lift does not masquerade as growth.
