Checkout Abandonment Rate (E-commerce)

Checkout abandonment rate measures the percentage of shoppers who start checkout but don’t complete the purchase. It’s one of the most cited “funnel leak” metrics,
yet it’s also one of the easiest to misreport because “checkout started” can be tracked in different ways across analytics tools and platforms.

Back to the hub:
E-commerce Statistics.
For context and triangulation, compare with
cart abandonment rate,
conversion rate (CR) benchmarks,
and payment failure rate benchmarks.

Metric: Checkout abandonment rate
Silo: Conversion funnel benchmarks

Key benchmark (cite-ready)

The most commonly cited cross-industry reference point for checkout abandonment is a range rather than a single number.
Use it as a benchmark reference, not a target: category mix, device mix, and checkout UX can shift rates dramatically.

Typical checkout abandonment range
60%–80%
Cross-industry range used in reporting (10-year framing)

Why this range matters
High intent
Checkout drop-offs happen late in the funnel, so they usually represent higher revenue leakage per session.

Context metric (cart → purchase)
70.22%
Average documented cart abandonment (multi-study average)

If you need a single-number headline, prefer the range (60–80%) and then immediately qualify it with your segment (device + category).
Avoid mixing “cart abandonment” with “checkout abandonment” — they are different denominators.

Segment benchmarks (what actually changes the number)

One benchmark can’t describe the whole market. Use this segment structure so your reporting stays comparable and citation-safe.

Segment What to report Why it matters Pair with
Device (mobile / desktop / tablet) Checkout abandonment by device Mobile friction (form fill, performance, authentication) often increases drop-offs. mobile revenue share
Checkout boundary What event counts as “checkout started” Some setups count “view checkout”, others “begin checkout”, others “shipping step started”. methodology
Category / vertical Checkout abandonment by category Category affects pricing, returns anxiety, delivery expectations, and fraud screening. return rate
Market / region Country/region + local payments Local methods and SCA/3DS patterns change completion and payment failures. payment methods share
New vs returning First-time vs returning checkout abandonment Returning buyers often complete more efficiently; new buyers are more sensitive to trust and surprises. repeat purchase rate
Payment reliability Payment failure rate alongside abandonment Some “abandonment” is actually a failed transaction (declines/errors/authentication). payment failure rate
READ  Conversion Funnel Benchmarks (E-commerce Statistics)

Device split (example benchmark set)

Use device-specific reporting whenever you cite checkout abandonment. It’s the fastest way to make the number “real” and comparable.

Device Abandonment rate (benchmark) How to interpret
Desktop 73.07% Best completion environment, lower friction, higher “sit-down intent”.
Tablet 80.74% Often closer to browsing behavior; form/UI friction still present.
Mobile 85.65% Highest friction: typing, distractions, performance, payment authentication.

Important: device benchmarks are only comparable when “checkout started” is defined the same way across sources and implementations.

Top reasons shoppers abandon during checkout (distribution)

This “reason layer” is what makes articles linkable: it explains the “why” behind the benchmark.
The distribution below is widely cited in e-commerce reporting and maps directly to checkout-stage friction.

Reason (checkout-stage friction) Share of shoppers What to do with it (reporting angle)
Extra costs too high (shipping, tax, fees) 39% Use this when writing about transparency, shipping policy, and total-cost disclosure.
Delivery was too slow 21% Use when connecting checkout to delivery options and delivery speed expectations.
Didn’t trust the site with card details 19% Use for trust signals, payment branding, and security reassurance.
Site wanted the shopper to create an account 19% Use for guest checkout prominence and account step design.
Too long / complicated checkout 18% Use to justify form reduction, autofill, and reducing steps.
Returns policy wasn’t satisfactory 15% Use for returns clarity and policy placement near checkout.
Website had errors / crashed 15% Use for performance, reliability, and checkout monitoring.
Couldn’t see / calculate total cost up-front 14% Use to support total-cost calculators and early disclosure.
Not enough payment methods 10% Use to justify local methods (wallets, transfers, BNPL) by market.
Credit card was declined 8% Use to connect checkout abandonment with payment failure monitoring.
READ  Checkout Completion Rate (E-commerce)
Checkout-specific evidence points used frequently in reporting:
a meaningful share of shoppers abandon due to account creation friction, and a meaningful share abandon due to a long/complicated checkout.

Definition and calculation

Checkout abandonment is a “late-funnel” rate. Always specify what counts as “checkout started”.

Checkout abandonment rate is commonly calculated as:

Checkout abandonment = 1 − (Orders completed ÷ Checkouts started) × 100

  • Checkout started can mean: view checkout, begin checkout, shipping step started, payment step started.
  • Orders completed should be defined consistently (paid vs created) in your analytics.
  • Don’t mix this metric with cart abandonment (different denominator).

Reference pages: GlossaryMethodology

How to report checkout abandonment (so it stays comparable)

If you publish this metric, include these fields next to the number.

  • Time window: month/quarter + year
  • Geography: country/region (and whether cross-border checkout is included)
  • Device split: at least mobile vs desktop
  • Checkout boundary: what event defines “checkout started”
  • Payment mix: include a link to payment methods share
  • Reliability: include payment failure rate when possible

If your goal is content that attracts citations, publish the benchmark + definition + sources in one place (this page) and link to it from related pages.

Sources

Primary and widely cited sources used for the benchmark ranges, device splits, and reason distributions.

READ  Categories & Demand (E-commerce Statistics)

Hub-wide references: SourcesMethodology

Cite this page

Copy and paste.

Best for Ecommerce. (2026). Checkout abandonment rate (e-commerce). Retrieved from
/ecommerce-statistics/conversion-funnel/checkout-abandonment-rate/

Jakub Szulc

I am an active Ecommerce Manager and Consultant in several Online Stores. I have a solid background in Online Marketing, Sales Techniques, Brand Developing, and Product Managing. All this was tested and verified in my own business activities

Recent Posts