This report is built from anonymized order and revenue data captured across Shopify stores in Shogun’s network. A store is included if it recorded at least 375 orders from January through September 2026. Stores with an average order value above $5,000 are excluded as non-representative of the mainstream ecommerce market.

Benchmark figures (medians, means, and percentile ranges) reflect 2,819 active stores. Quarter-over-quarter figures compare only stores active in both Q2 and Q3 2026 with at least 125 orders in each quarter. Year-over-year figures compare only stores active in both January–September 2025 and January–September 2026. Within-quarter monthly trend figures compare only stores active in all three months of Q3 with at least 50 orders per month. Industry categories are derived from Storeleads data using Google Product Taxonomy classifications, and revenue bands are based on Storeleads estimated annual GMV; both are third-party estimates.

Across 2,819 active stores in 2026 so far, the median AOV is $313 and the mean is $614. The middle 50% of stores fall between $159 and $692. A “good” AOV depends heavily on your industry — Autos & Vehicles stores have a median of $601, while Health & Wellness and Food & Beverage stores sit at $174. Use your industry-specific median as the reference point, not the cross-industry figure.

AOV equals total order value divided by total orders. We calculate it at the store level — summing each store’s orders and order value across every month in the reporting period, then dividing the totals — rather than averaging each month’s AOV.

The median across our 2,819-store dataset is $313. The mean is $614 — roughly double the median — pulled higher by a persistent right tail of high-AOV merchants, particularly in Autos & Vehicles, Consumer Electronics, and Business & Industrial. For benchmarking your own store, use the median.

Autos & Vehicles (median $601), Consumer Electronics (median $479), and Business & Industrial (median $450) lead the dataset in 2026 so far. These are considered-purchase or higher-unit-price categories where customers commit to fewer, larger transactions.

Health & Wellness and Food & Beverage (both with a median of $174) and Beauty & Personal Care (median $274) have the lowest medians. These are repeat-purchase categories with lower per-unit prices — and they’re also the categories where conversion rates tend to run highest.

As more of the year came into view, the AOV picture became more nuanced. Year over year, same-store matched AOV rose a modest 3.3% ($309 to $319), with four of nine reported categories posting gains, led by Autos & Vehicles (+17.9%) and Beauty & Personal Care (+7.8%), while others now trail the prior year. Quarter over quarter, AOV grew 4.6% from Q1 to Q2, then held flat from Q2 to Q3 ($311 in both quarters). Within Q3, the median was $306 in July, $300 in August, and $307 in September.

Start with your industry’s median, then work toward its P75 — cross-industry comparisons are usually the wrong benchmark, since a $300 AOV can be strong in one category and weak in another. Revenue scale matters too: enterprise stores ($50M+ GMV) post a $381 median AOV, 30% higher than stores below $15M ($292), largely reflecting product mix, bundling, and upsell maturity rather than traffic differences.

Median. It describes the typical merchant and isn’t pulled around by a handful of very high-ticket outliers. The mean is useful as a diagnostic — in this dataset it runs well above the median in every category and about double it overall, which signals a persistent right tail. When mean and median move together, a trend is broad-based; when they diverge, the cohort shape is changing.

Not on its own. Our data shows an inverse pattern: the categories with the highest conversion rates — Health & Wellness, Beauty & Personal Care, Food & Beverage — tend to have the lowest AOVs, and the reverse holds for Autos & Vehicles and Business & Industrial. Apparel & Accessories is a notable middle case, pairing an above-median AOV with a conversion rate close to the cross-industry median. AOV and conversion rate are both levers on revenue, and optimizing one in isolation can work against the other.

No, not directly. The AOV data here comes from full Shopify order data across tracked merchants, while the conversion rate benchmark is based on Shogun-instrumented session data — a different and non-overlapping universe of stores and traffic. Multiplying conversion rate by AOV across the two reports would not produce an accurate revenue-per-session figure. Treat them as separate benchmarks answering separate questions.