Average Order Value by Industry

Average order value by industry is a reference for basket spending, rather than a target your store must reach. In these Shopify benchmarks, cosmetics sits at $50, clothing at $113, and decor and furniture at $165. These industry medians draw on hundreds of Shopify stores in total, covering approximately July 7 through October 7, 2026, in US dollars.

Start with the closest product group, then look at the range around its midpoint. Larger baskets can reflect higher product prices, different customers, or useful offers. They do not establish that a store earns more profit.

What does average order value tell you?

Average order value, or AOV, tells you what customers spend per order during a chosen period. It describes purchases, rather than spending per customer over their relationship with your store. A customer placing several small orders can be valuable despite a modest basket.

To find your own AOV, choose a reporting period and divide its sales revenue by its order count. Check the revenue description in your report before comparing it with another source. Taxes, shipping, discounts, and refunds can change what a reported order value means.

Keep the dates and currency consistent when reviewing your own trend. Comparing a normal trading period with a major sale can confuse an offer's effect with seasonal demand. Write down the report you used so the next comparison starts from the same measure.

The charts below show the median, meaning the middle store, and the range around it. The range describes the middle half of stores. It helps you see whether the midpoint represents a tight cluster or a much wider set of businesses.

Start with your product category

Choose a broad category first, then narrow the comparison where a more suitable industry appears below. The health and beauty midpoint is $69, while home and garden sits at $154. Both describe broad groups whose products and purchase occasions can differ considerably.

Electronics has a higher midpoint than food and drink in this comparison. That is a reason to choose peers carefully, rather than a verdict on either category's performance. Product price and purchase frequency matter when deciding whether a larger basket is desirable.

For context beyond order value, see our ecommerce benchmarks for Shopify stores. Refunds and repeat buying answer different questions about the value of those orders.

Find a closer industry reference

Cosmetics and skincare have different midpoints, so one beauty target can send an operator toward the wrong comparison. Cosmetics sits at $50, while skincare and accessories sits at $77. These industry references cover the same approximate period stated above.

These figures do not measure the effect of a bundle or explain why shoppers spend more on skincare.

The table is also useful for replenishment businesses. Coffee and tea has a different reference from artisan and specialty foods, despite both belonging to food and drink. Compare similar prices, pack sizes, and buying occasions within your own business before deciding what to test.

A missing industry has no usable reference in this table. It does not mean the industry has no sales or that its order value is zero. Use your own consistent history when the available product groups are a poor match. Industries with fewer stores give a rougher reference, so treat their medians as a guide rather than a benchmark to hit.

Read the furniture range before setting a target

Decor and furniture has a wide range, so the midpoint alone gives an incomplete view of comparable businesses. The median is $165, with a middle range from $97 to $421. That is a substantial difference in basket spending within one industry label.

For comparison, cosmetics has a middle range from $38 to $71, a much narrower spread. The furniture midpoint leaves more variation unexplained, so inspect your product mix before choosing a target.

A store selling small decorative pieces faces different purchase decisions from a store selling large furniture. Think about whether shoppers buy a single item, a matching set, or pieces for an entire room. The industry range cannot tell you which business model explains a particular store's result.

Use the upper part of the range as a prompt to inspect your assortment. If complementary products solve a useful customer need, a set may deserve testing. If the comparison mainly reflects expensive products, pushing customers toward more items could add friction without improving profit.

Why other benchmark sources give different answers

Different benchmark sources describe different businesses and periods, so their headline values need context. Littledata's AOV benchmarks show Shopify industry and device comparisons. Dynamic Yield's order value dashboard offers global, regional, and industry views.

Those are useful alternative references when their audience and period fit your question. They do not establish that a difference from this table is an error. Check the source's dates, currency, and description before combining figures in a planning document.

Device and geography deserve separate attention in your own reports. Mobile visitors may arrive with different purchase intentions from desktop visitors. Shipping costs, local prices, and the countries you serve can also affect basket spending.

Wholesale needs its own comparison too. A business buyer restocking supplies has a different reason to place a large order than a consumer buying a gift. These tables do not provide a matched wholesale, country, or device comparison.

Seasonal offers can change which products sell together and how much shoppers spend. Keep major promotions separate when checking your normal baseline. This snapshot does not establish a seasonal trend or tell you what next year's order values will be.

Choose an AOV goal that protects profit

Choose a goal from an identifiable opportunity in your store, rather than copying the industry's upper range. Start with your current order value, the products customers buy together, and the costs of fulfilling those orders. A useful goal gives you a specific offer to test.

Keep conversion rate beside AOV when reviewing the result. A larger basket with fewer completed purchases can leave the business worse off. Look at revenue per visitor to see whether the offer helps the traffic you already have.

Then check what remains after discounts, product costs, fulfillment, and delivery. An offer can increase order value while leaving less money to cover the business. Review returns as well if the offer encourages customers to buy products they may not keep.

Repeat purchases add another check for replenishment brands. A large initial supply may raise today's basket while delaying the next purchase. Review the customer relationship before assuming the larger first order is the better outcome.

For example, test a cleanser and moisturizer pairing against the same products sold separately. Keep it if more customers complete a useful purchase and the money remaining after costs improves. A higher basket alone would leave that decision unresolved.

Choose the measures that fit your decision with our guide to ecommerce metrics and KPIs for Shopify. A Shopify KPI dashboard can help keep the selected measures visible together.

Test an offer that fits the purchase

Start with a relevant offer that makes the customer's intended purchase easier. For a skincare store, a routine pairing might be more useful than an unrelated discounted item. For coffee, complementary products or a sensible pack size could suit how customers already buy.

Shipping thresholds deserve their own cost check. Choose a threshold customers can reach with products they want, then review the shipping cost you absorb. An industry AOV does not tell you the right threshold for your delivery economics.

Subscriptions fit products people use regularly and want to replenish. They are less useful for occasional purchases or gifts. A loyalty offer should reward a useful purchase rather than encourage spending that leaves the customer with unwanted products.

Test one change at a time and record which customers saw the offer. Compare order value, completed purchases, and profit with the same measures used for your baseline. Keep the offer only if the wider results support it.

By the Numbers includes an Average Order Value report for reviewing order spending over time. See ecommerce reporting when you need a place to examine your store's results alongside other sales measures.

How we measured these benchmarks

These benchmarks use anonymized, aggregated data from Shopify stores in the By the Numbers network. No individual store is identifiable from any figure. Stores that use an analytics app are not a random sample of all Shopify stores, so read the figures as a reference point, not as an average for the whole market.

Keep reading

If you want the full picture on ecommerce metrics and KPIs, start with the KPIs that actually move Shopify revenue.

Related reading: How to Build an Ecommerce KPI Dashboard for Shopify, Best Shopify Analytics Plan For Store Growth and 7 Common Shopify Analytics Mistakes to Avoid.

By the Numbers builds this into the dashboard. See Shopify ecommerce reporting.