Ecommerce conversion rate benchmarks

Ecommerce conversion rate, average order value, add-to-cart and cart abandonment benchmarks, each with the sample, market and period the publisher states.

Store conversion rate is the most misquoted number in ecommerce, because the honest version has three qualifiers: which market, which device, and which month. The current table here covers B2C stores in Great Britain and Ireland in July 2026, where the overall rate is 2.26% and the average order is £123.37.

Category range inside a single month is larger than most year-on-year movement: Arts and Crafts converts at 5.23% and Baby & Child at 0.55%, the latter on a £737 average order. A low rate on a high-value, considered purchase is not a problem to fix.

The device split and the add-to-cart ratio come from an older Shopify dataset, kept because the structure it shows — desktop converting roughly 1.6× mobile, 4.6% of sessions adding to cart — holds up better over time than the absolute level does. Cart abandonment is a meta-analysis of 50 studies, not a single measurement.

Ecommerce conversion rate & AOV — UK & Ireland

Who is in this sample: B2C stores on the IRP platform in Great Britain, Northern Ireland and Ireland, July 2026

IndustryCVRAOV
Arts and Crafts5.23%£122.78
Health and Wellbeing3.57%£51.55
Kitchen & Home Appliances3.34%£53.73
Pet Care2.95%£80.79
Sports and Recreation2.12%£107.12
Cars and Motorcycling1.82%£212.96
Fashion Clothing & Accessories1.81%£82.08
Toys, Games & Collectables1.72%£64.81
Food & Drink1.47%£106.77
Baby & Child0.55%£737.47
All markets · publisher's own figure2.26%£123.37

Industry names are reproduced in the publisher's own wording.

Source

Publisher
IRP Commerce
Data period
July 2026
Sample
First-party platform data, aggregated; store count not disclosed
Geography
Great Britain, Northern Ireland and Ireland
Statistic
Figures are averages

Notes on this table

  • B2C only, and values are published in pounds sterling.
  • The report's 'cost per acquisition' column is a percentage of revenue, not a per-order cost, and is not reproduced here.
  • Values are in pounds sterling, not dollars.
  • This is a single month. The publisher's July 2025 comparison shows swings of a full percentage point in several markets, so read one month as a snapshot rather than a trend.

Shopify conversion rate, AOV & add-to-cartDated

Who is in this sample: 2,800 Shopify stores, 2023

IndustryCVRAOVATC
All devices1.4%$85.004.6%
Desktop1.9%
Mobile1.2%
Food & Beverage1.5%4.8%
Fashion1.9%5.4%
Travel0.2%
Finance0.2%

Industry names are reproduced in the publisher's own wording.

Source

Publisher
Littledata
Data period
2023
Sample
2,800 Shopify stores
Geography
Not stated
Statistic
Figures are averages

Notes on this table

  • Shopify stores only.
  • No tablet figure is published — mobile and desktop only.
  • Rows mix devices and verticals because that is how the publisher segments this dataset.
  • The top 10% of Shopify stores convert at 4.7% against the 1.4% average — the distribution is heavily skewed, so an average alone is a weak target.
  • The publisher's cross-ecommerce average order value is $101; the $85 above is the Shopify-only figure.
  • 2023 data. Treat it as a structural reference (device gap, add-to-cart ratio), not as a current number.

Cart abandonment

Who is in this sample: Meta-analysis of 50 studies published 2006–2025

IndustryAbandonment
Documented average across 50 studies70.22%

Industry names are reproduced in the publisher's own wording.

Source

Publisher
Baymard Institute
Data period
Meta-analysis of studies published 2006–2025
Sample
50 separate studies; individual study results range 55.00%–84.27%
Geography
Mixed
Statistic
Figures are averages

Notes on this table

  • An average across 50 studies of differing age, method and geography, not a single measurement.
  • Individual studies in the set range from 55.00% to 84.27%; the headline figure is their average.
  • Of shoppers who abandon for a reason other than browsing, the publisher's survey attributes 40% to extra costs (shipping, tax, fees), 20% to slow delivery, 19% to payment trust, 18% to forced account creation and 17% to a long checkout.

How to use these numbers

A benchmark is a description of someone else's sample, not a target. The number worth hitting is your own break-even: the cost per acquisition your margin allows, or the return on ad spend that leaves a profit after the product is paid for. Use the calculators to work that out first, then use the benchmark to ask whether the market is even priced for it.

When your number sits far from the table, check the sample before checking your account. A store compared with a lead-generation sample, or a brand-heavy account compared with broad prospecting, will look broken while being perfectly healthy. The universe line above each table is there for exactly that check.

Calculators for these metrics

Frequently asked questions

What is a good ecommerce conversion rate?
In the current UK and Ireland sample, 2.26% is the middle. But the top decile of Shopify stores converts at 4.7% against a 1.4% average in that dataset, so the distribution is skewed enough that an average makes a weak target. Your own trend line, split by device and traffic source, is the better comparison.
Why is my mobile conversion rate so much lower than desktop?
It is lower for nearly everyone: 1.2% against 1.9% in the Shopify sample. Mobile carries more discovery traffic and more interrupted sessions. The number to watch is the gap over time, not the gap itself.
Is a 70% cart abandonment rate normal?
It is the documented average across 50 studies, which individually range from 55% to 84%. The publisher's own survey attributes 40% of non-browsing abandonment to extra costs at checkout, 19% to payment trust and 18% to forced account creation — all fixable, unlike browsing behaviour.

How this data is handled

  1. Every figure is transcribed from a public report and carries its publisher, sample, data period and a link. Nothing is estimated or rounded to “about”.
  2. Publishers are never blended. A click-through rate from one report and a CPM from another never appear in the same row.
  3. Each table states who is in its sample, because advertiser mix — not disagreement — explains most of the spread between reports.
  4. Publisher errors and dated datasets are footnoted rather than quietly corrected or refreshed from another source.

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