Industry Benchmarks Benchmarks
Cross-vertical benchmarks for conversion rate, AOV, cart abandonment, and repeat-purchase rate — with guidance on which neighbouring categories are worth borrowing tactics from.
Industry Benchmarks
Cross-vertical reference values for conversion-related metrics — CR, AOV, cart abandonment, repeat-purchase rate — used to judge whether your store is over- or under-performing its category.
Industry benchmarks are aggregated metric ranges drawn from a population of online stores, usually segmented by vertical (apparel, beauty, electronics, home, food & beverage, supplements). They answer the only question that matters when you stare at your own number in isolation: is this good?
Useful benchmarks compare like-for-like. A 1.8% conversion rate is poor for a beauty store stocking a hero SKU at €29, and excellent for a furniture store with a €1,400 AOV. Benchmarks let you frame performance against the right peer group — and, more usefully, spot which adjacent category is doing something you could borrow.
Four metrics carry most of the diagnostic weight in e-commerce: conversion rate (what share of sessions buy), average order value (how much each order is worth), cart abandonment rate (how leaky checkout is), and repeat-purchase rate (whether customers come back). Each one moves differently across verticals, so a single "good" number doesn't exist.
Beauty stores live or die on repeat rate because the unit price is small. Furniture stores tolerate a 0.6% conversion rate because a single sale clears €1,000. Supplements lean on subscription to lift LTV past the CAC line. The benchmark table below is the starting frame — your job is to find your row, then look one row above and one row below to see what's possible.
Conversion metrics by DTC vertical (median ranges)
| Vertical | Conversion rate | AOV | Cart abandonment | Repeat-purchase rate (12mo) |
|---|---|---|---|---|
| Beauty & Personal Care | 2.4% – 3.6% | €38 – €65 | 68% – 74% | 38% – 48% |
| Apparel & Accessories | 1.6% – 2.8% | €55 – €95 | 70% – 78% | 28% – 36% |
| Health & Supplements | 2.8% – 4.2% | €42 – €78 | 65% – 72% | 45% – 58% |
| Food & Beverage | 2.0% – 3.4% | €32 – €58 | 66% – 73% | 40% – 52% |
| Home & Garden | 1.2% – 2.0% | €85 – €180 | 72% – 80% | 18% – 26% |
| Electronics & Gadgets | 0.9% – 1.6% | €120 – €260 | 75% – 82% | 14% – 22% |
| Furniture & Décor | 0.4% – 0.9% | €280 – €1,400 | 78% – 86% | 10% – 18% |
| Pet Supplies | 2.6% – 3.8% | €38 – €68 | 67% – 73% | 44% – 56% |
Two patterns jump out. First, conversion rate and AOV trade off — high-ticket categories convert less often, low-ticket categories convert more. Second, repeat rate clusters around consumable categories (beauty, supplements, food, pet) and collapses on considered durables (furniture, electronics). Compare yourself to your vertical first, then to the consumable-vs-durable cluster you belong to.
Median conversion rate by vertical
How to read the spread, not just the number
Benchmarks express a range because the spread inside a vertical is usually wider than the gap between verticals. A top-quartile apparel store converts at 2.8%; a bottom-quartile one converts at 1.0%. That 2.8x gap is where the real lessons live — not in the median.
If you're below median on conversion rate but above median on AOV, you're probably leaving volume on the table with hesitation around price — bundle pricing, financing, or trust signals at checkout move the needle. If you're above median on CR but below on AOV, the opportunity is post-add-to-cart: upsells, free-shipping thresholds, and cross-sell modules. The pattern of where you sit, not the absolute number, prescribes the work.
Don't benchmark against a vertical you don't belong to
If you sell candles at €24 each, your peer set is beauty and home fragrance — not "home & garden," which is dominated by patio furniture and large-ticket décor. Mis-bucketing your vertical produces targets that are either too easy (you'll celebrate mediocre performance) or impossibly hard (you'll burn budget chasing them). Pick the segment whose unit economics — AOV, purchase frequency, consideration time — actually matches yours.
Turning benchmarks into a roadmap
Benchmarks are most useful when you treat them as a diagnostic, not a scoreboard. Plot your four metrics against the vertical median, mark the biggest gap, and that gap is your next quarter's priority. A 4-point cart abandonment gap on a €60 AOV store with 200k sessions a month is roughly €60k in recoverable revenue — bigger than most homepage redesigns ever produce.
Look one rung up the ladder for tactics. A beauty store wanting to move from 2.4% to 3.2% should study what supplement brands do with subscription onboarding, replenishment reminders, and loyalty tiers. An apparel store stuck at 1.6% should study how beauty handles bundle merchandising and reviews above the fold. Neighbouring categories share enough mechanics to be borrowable and enough difference to be novel.
Frequently asked questions
Quarterly is the right cadence for strategy reviews. Benchmarks don't shift fast enough month-to-month to be worth chasing, but a year of compounding drift — say, AOV inflation pushing your category up €8 — can quietly leave your targets stale.
Pick the one that matches your unit economics, not your product taxonomy. A premium skincare brand at €120 AOV behaves more like apparel than mass-market beauty. Weight by where most of your revenue comes from and use the secondary vertical only as a sanity check.
The ranges shown are weighted toward Western European and North American Shopify and WooCommerce stores. APAC and LATAM stores typically run lower AOVs and higher abandonment, while Nordic markets skew toward higher AOV and lower CR. Adjust your reading by 10-20% if you're outside the core regions.
Sub-€1M Shopify stores typically sit at the lower end of their vertical's range — usually 60-80% of the median. The gap closes as traffic quality stabilises past €1M, when paid and email channels are dialled in and brand search becomes a meaningful share.
Probably normal. The 60-80% band is where almost every category lives, because "abandonment" includes researchers, price-checkers, and returning visitors who never intended to buy on that session. Focus on completed-checkout abandonment (people who entered email and dropped) — that's the metric where 10-20% is good and 40%+ is fixable.
Direct-to-consumer typically outperforms marketplace channels on repeat rate by 1.5-2x because you own the email list and post-purchase flow. The trade-off is acquisition cost — marketplaces hand you a buyer, your own site has to earn them — which is why most brands run both and benchmark them separately.
Whichever has the bigger gap to your vertical median. If you're 30% below on CR and 5% below on AOV, fix CR. If both gaps are similar, AOV tactics (bundles, free-shipping thresholds, upsells) usually ship faster and don't require splitting traffic for tests.
Significantly. Subscription stores typically show lower first-purchase conversion rates (1.2-2.0%) because the commitment is heavier, but repeat rate and LTV are dramatically higher. If you offer both, segment your funnel by intent and benchmark each path separately.
Start with vertical medians as your 90-day target, not your launch number. New stores typically open at 50-60% of vertical median CR and climb as traffic mix stabilises. Importing historical GA4 data — even a year of it — lets you skip the cold-start period when planning experiments.
Year-over-year improvement matters more for operational health; vertical benchmark matters more for strategic ceiling. A store improving 15% YoY but still 40% below vertical median has a structural problem no amount of incremental optimisation will fix — usually positioning, pricing, or product-market fit.
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