2026 Benchmarks

E-commerce Benchmarks 2026

The operator reference for subscription and DTC e-commerce. Conversion rate, average order value, cart abandonment, retention, and subscription churn - segmented by industry, price band, country, and device, with the formula and the calculation mistake for each. Figures represent aggregate 2026 industry data; use category-specific ranges rather than a blended average.

Conversion rate by industry

The global average e-commerce conversion rate sits between 2% and 3% in 2026, but the spread by industry is 8x. Low-price, high-frequency categories convert several times higher than high-consideration ones, because purchase friction scales with price.

IndustryConversion rateWhat drives it
Food & beverage4.5-6.2%Highest converting. Low price, high frequency, low purchase friction.
Beauty & personal care2.5-3.5%Among the highest. Replenishment and habitual purchase drive repeat conversions.
Health & supplements2.5-3.5%Subscription intent lifts conversion above one-time verticals.
Apparel & fashion2.0-3.0%Mid-pack. Fit uncertainty and returns suppress the rate.
Home & furniture1.0-2.0%High AOV, long consideration. Converts low but each order is large.
Electronics1.5-2.5%High-consideration purchases with heavy price comparison.
Luxury & jewelry0.8-1.5%Lowest conversion, highest AOV. Discovery and trust dominate.

Conversion rate by country and region

Geography moves conversion as much as category. Germany leads individual countries on high-trust checkout behavior; EMEA leads regionally. A brand comparing its rate to a global average without adjusting for its traffic mix will misread its own performance.

MarketConversion rateWhat drives it
Germany2.2%Top country. High-trust, high-intent purchase culture; direct debit and BNPL.
United States2.0%Large market, mobile-heavy traffic pulls the blended rate down.
United Kingdom1.9%Strong mobile checkout adoption; fast-delivery expectation.
EMEA (region)3.1-4.1%Leads regional averages on desktop-weighted, high-trust markets.
Americas (region)3.1%Second regionally; wide spread between US and LATAM.
APAC (region)1.5-2.5%Mobile-first, price-sensitive; lower blended conversion.

Average order value by industry

Global AOV reached roughly $150-180 in 2026, but the vertical spread runs from luxury above $400 to food under $50. AOV and conversion move in opposite directions: the categories that convert highest have the smallest baskets.

AOV = Total Revenue / Number of Orders

IndustryAOV rangeWhat drives it
Luxury & jewelry$180-436Highest AOV. A single order can exceed a month of another vertical.
Electronics$120-348High ticket, low frequency. AOV carries the economics.
Home & lifestyle$95-295Large baskets, long cycle. Cross-sell matters more than reorder.
Fashion & apparel$80-200Wide range by positioning; premiumization pushing the top up.
Food & beverage$45-147Low AOV offset by the highest purchase frequency.
Beauty & personal care$55-137Bundling and replenishment lift basket size.
Pet$55-110Autoship stabilizes AOV and drives most category revenue.
Supplements$45-120Subscription bundling is the main AOV lever.

AOV by region and device

Region and device shift AOV independently of category. Desktop orders run larger than mobile despite mobile carrying most traffic, and EMEA baskets exceed APAC by more than half.

SegmentAOVContext
Global average$150-180Blended across all verticals and regions; up 5-8% over 2024.
EMEA$193Highest region. Higher basket sizes and premium positioning.
Americas$158Mid-range regionally.
APAC$125Lowest region; high frequency, small baskets.
Desktop$192Desktop shoppers still spend more per order.
Mobile$133Majority of traffic, smaller baskets; the checkout-friction gap.
DTC median (paid channels)$74Top 20% of Shopify stores exceed $120; bottom 20% under $50.

Cart abandonment by device and industry

The global cart abandonment rate is 70.2%. The device gap is the largest lever: mobile abandons at 80% against desktop at 66%, and that gap has survived years of mobile-first checkout work. Fashion and luxury abandon highest; replenishment categories lowest.

Cart Abandonment Rate = 1 - (Completed Purchases / Carts Created)

SegmentAbandonmentWhat drives it
Global average70.2%Baymard meta-analysis of 49 studies. The baseline every store fights.
Mobile80.0%The persistent gap. Checkout friction survives years of mobile-first work.
Tablet71.2%Between mobile and desktop.
Desktop66.4%Lowest device abandonment; larger screens, saved payment methods.
Fashion84.6%High abandonment. Size and fit uncertainty drive drop-off at checkout.
Luxury & jewelry82.8%High-consideration, high-ticket; long deliberation before purchase.
Beauty & personal care80.9%Discovery-heavy browsing inflates cart-add-to-purchase drop.
Pet & grocery50-55%Lowest abandonment. Replenishment intent is high and repeat.

Retention and repeat purchase by industry

E-commerce retention averages 30-31% across industries, but ranges from luxury near 10% to subscription boxes at 60-70%. A 5% increase in retention can lift profit 25-95%, and repeat customers spend more per order than new ones - which is why this metric sits close to survival.

Repeat Purchase Rate = (Customers With More Than One Purchase / Total Customers) x 100

VerticalRepeat / retentionWhat drives it
Subscription boxes60-70%Highest retention. Cancel-flow and pause-vs-cancel design set the curve.
Grocery & food delivery~65%Repeat-purchase intent leads all categories; 40% shop weekly.
Consumables (replenishment)40-55%Failure mode is involuntary churn from failed payments.
Pet supplies30-40%Autoship compounds retention; drives the majority of category revenue.
Beauty & cosmetics30-40%Replenishment timing and education content drive the lift.
Fashion & apparel25-32%Seasonal cadence; first-to-second purchase window is the lever.
Luxury fashion~10%Lowest repeat. Purchases are occasional and considered.

Full breakdown in e-commerce retention rate benchmarks and repeat purchase rate.

Subscription churn by category and billing period

The average monthly churn for DTC subscription in 2026 is 6.5-8.5%. Replenishment categories (supplements, consumables, pet) run 5-8%; curation categories (beauty and apparel boxes, meal kits) run 8-15%. The single largest lever is billing period: annual billing cuts monthly-equivalent churn by 60-80% on the same product.

Monthly Churn Rate = (Subscribers Lost During Month / Subscribers Eligible to Churn) x 100

CategoryMonthly churnWhat drives it
Supplements5-8%Replenishment category. Low churn once habit forms in first 60 days.
Household consumables5-8%Necessity-driven; involuntary churn is the main leak.
Coffee5-10%Habitual, but taste fatigue and pantry-loading cause pauses.
Pet6-10%Sticky once autoship is set; cancellation is deliberate.
Beauty boxes8-14%Curation category. Novelty fatigue drives the higher range.
Meal kits8-15%Highest churn. Delivery friction and menu fatigue compound.

Full breakdown in churn rate benchmarks by industry.

Unit economics targets

Conversion, AOV, and retention feed one question: is each customer profitable on a standalone basis? These are the targets that answer it. Most DTC brands calculate them on revenue rather than contribution margin, which hides the acquisition math that determines whether scaling is safe.

MetricTargetWhat it measures
Contribution margin30-50% of net revenueAfter COGS, shipping, payment fees, returns. The number that funds acquisition.
LTV:CAC ratio3:1 to 5:1Below 3:1 loses money; above 5:1 underinvests in growth. Compute LTV on margin, not revenue.
CAC payback periodUnder 12 monthsMonths to recover acquisition cost from contribution margin. Under 6 is strong.
Involuntary churn share20-40% of total churnThe share recoverable by dunning. Above 40% is a payment problem, not a product one.
Dunning recovery rate50-70% of failed paymentsBelow 40% signals a missing card updater or one-size-fits-all retry timing.

Full breakdowns: LTV:CAC ratio, unit economics, and automated dunning.

See where your brand sits against these

Benchmarks tell you what good looks like. Finsi computes your actual conversion, AOV, retention, and churn composition from your order and subscription data, so you see which of these numbers you are winning and which you are losing against your own category. Book a demo to see your figures against this reference.

Sources and methodology

Figures are aggregated from published 2026 industry data, including Baymard Institute (cart abandonment meta-analysis of 49 studies), Shopify and Triple Whale merchant benchmarks, Statista country conversion data, and category retention and churn studies. Ranges are given rather than point estimates because methodology varies across sources; treat them as comparison bands, not exact figures. Where a brand's own number falls inside a band is less informative than which direction it is moving quarter over quarter. Last updated July 2026.