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Baymard Institute’s latest published pooled benchmark puts online shopping cart abandonment at 70.22%, based on 50 studies. Its statistics page is titled for 2026 but was last updated September 22, 2025, so this is not a newly measured 2026 global rate. It is an industry benchmark—not a forecast for any one store.
What percentage of people abandon their carts and don’t complete their purchase?
The direct answer is 70.22% in Baymard Institute’s average of 50 documented studies. The figure describes the share of online shopping carts abandoned in the studies Baymard compiled; it should not be read as a live measurement of every ecommerce site or as a target every store should expect to match. Baymard’s cart abandonment statistics labels the page “2026,” but gives its last update as September 22, 2025.
A store’s own rate depends on how it defines a cart, what event counts as abandonment, and which shoppers and time period are included. A cart left before checkout is not necessarily the same event as a checkout started but not completed. Without matching those definitions, comparing a store’s analytics with a published average can mislead.
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Not every abandoned cart signals a problem that a merchant can fix. Baymard reports that 42% of US online shoppers in its latest quantitative study had abandoned a cart because they were “just browsing / not ready to buy.” People may be comparing prices, saving items for later, window-shopping, or exploring gift options. The result is reported shopper behavior, not a measure of recoverable sales.
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Baymard presents its other abandonment reasons separately from this just-browsing group. The percentages below are reasons respondents gave, not mutually exclusive portions of all abandoned carts; they should not be added together. The reasons page was updated February 2, 2025 and calls this its latest quantitative study, so its “2026 data” label does not mean the survey was conducted in 2026.
| Reason reported | Share | Context |
|---|---|---|
| Extra costs too high | 40% | Baymard Institute, US shopper reasons data labeled 2026; browsing/not-ready responses excluded from this list. |
| Delivery too slow | 20% | Baymard Institute, same reasons data. |
| Distrust of site credit-card security | 19% | Baymard Institute, same reasons data. |
| Required account creation | 18% | Baymard Institute, same reasons data. |
| Checkout too long or complicated | 17% | Baymard Institute, same reasons data. |
| Website errors or crashes | 17% | Baymard Institute, same reasons data. |
| Unsatisfactory returns policy | 13% | Baymard Institute, same reasons data. |
| Could not see or calculate total cost up front | 12% | Baymard Institute, same reasons data. |
| Card declined | 10% | Baymard Institute, same reasons data. |
| Too few payment methods | 9% | Baymard Institute, same reasons data. |
The findings distinguish shopping intent from obstacles during a purchase. Costs, delivery expectations, trust, account requirements, complexity, and technical errors are practical areas to investigate; the survey figures do not establish that any particular change will recover a specified share of lost orders. See Baymard’s explanation of why users abandon their cart.
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Why abandonment statistics vary by country and method
Baymard’s reasons findings concern US online shoppers. Mastercard’s 2025 South Africa findings offer a country-specific perspective: respondents cited a long or complicated checkout at 37.3%, shipping fees at 31.3%, and declined credit cards at 27.9% as reasons for abandoned transactions. In Mastercard’s 2024 comparison, declined cards were cited by 52.2%.
Those South Africa figures are not directly comparable to Baymard’s US shopper responses. The populations, survey context, time periods, and potentially the definition of an abandoned transaction differ. They should not be combined into a new average or treated as a global ranking. Mastercard’s South Africa report shows why geography and payment conditions matter when interpreting the numbers.
What the benchmark says about checkout design
Baymard’s checkout benchmark evaluates 343 top-grossing US and EU ecommerce sites against more than 110 cart and checkout guidelines. In its current research overview, Baymard says 65% of sites were mediocre or worse and 2% were good. These figures describe that benchmark sample, not all online stores. They indicate that checkout usability issues are common in the evaluated sites, but do not prove that a benchmark rating predicts any individual store’s abandonment rate. Baymard’s checkout usability research overview details the benchmark scope.
Baymard also reports that 17% of US online shoppers said in its latest quantitative study that they had abandoned an order in the prior quarter because checkout was too long or complicated. In a separate benchmark observation, the average US checkout displayed 23.48 form elements by default, including 14.88 form fields. Its usability research describes an ideal flow that can use as few as 12 elements in one example. These measures provide context, but form count alone does not establish why shoppers abandoned orders or predict the effect of reducing fields.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How merchants can use the statistics
The 70.22% figure is a reference point, not a store diagnosis. A useful response is to examine where shoppers leave in the merchant’s own funnel, then investigate the most relevant friction rather than trying to eliminate all abandonment.
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- Define the event. Decide whether the store is measuring carts created, checkout starts, or another event, and use a consistent denominator and time window.
- Locate the drop-off. Use the store’s own funnel analytics to determine whether shoppers leave at cart review, delivery and cost disclosure, account creation, payment, or after an error.
- Review the matching experience. Check whether full costs are visible early, delivery timing is clear, guest checkout is available, payment options are adequate, and checkout works reliably across devices.
- Test targeted changes. Make changes tied to observed drop-offs and compare outcomes against a suitable baseline. Treat transparent costs, guest checkout, and checkout-flow improvements as hypotheses to assess, not guaranteed conversion lifts.
Baymard’s guidance on reducing cart abandonment likewise emphasizes separating UX-related friction from other shopper behavior and identifying causes relevant to the store. Some abandonment is a natural consequence of browsing; the goal is to understand and reduce avoidable friction, not to assume every unpurchased cart represents a failed checkout.
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