Cart Abandonment Rate Calculator

Background.

Cart abandonment rate is the share of shopping carts that never turn into orders, and it is one of the few e-commerce metrics where the headline number is almost always quoted against the wrong denominator. Abandonment measured from add-to-cart and abandonment measured from checkout-started are different statistics with different values, and comparing your figure with a benchmark that used the other one is the most common way this metric misleads people. This calculator computes both, side by side, and shows the stage between them.

The funnel here follows Google Analytics 4's own recommended e-commerce events, so the numbers map onto something you can actually pull from a report: add_to_cart, which GA4 defines as signifying "that an item was added to a cart for purchase"; begin_checkout, "a user has begun a checkout"; and purchase. With 10,000 carts, 4,200 started checkouts and 1,450 orders, cart abandonment is 85.50%, checkout abandonment is 65.48%, and only 42.00% of carts ever reached checkout at all. That middle number is the one most stores never look at, and on this funnel it is where the larger absolute loss happens — 5,800 carts lost before checkout began against 2,750 inside it.

For context rather than a target: Baymard Institute publishes a running average of documented cart abandonment rates, currently 70.22%, calculated across 50 separate studies. Those studies do not agree with one another — the individual figures in Baymard's own list range from under 69% to nearly 80% — so treat the average as evidence that abandonment is normal and enormous, not as a line you have failed to clear.

The money outputs need reading carefully, and the caveat is printed next to them rather than hidden below. Multiplying abandoned carts by your average order value gives the value those carts held. It is a ceiling, not lost revenue. Baymard's quantitative study of reasons for abandonment found that 42% of US online shoppers have abandoned a cart because they were "just browsing / not ready to buy" — those shoppers were never going to check out, at any price, however good your recovery emails are. Among the shoppers who did intend to buy, Baymard's next-largest reasons are addressable: extra costs too high at 40%, delivery too slow at 20%, not trusting the site with card details at 19%, and being forced to create an account at 18%.

That is why the recovery rate is an input you control rather than a constant this page asserts. Enter what your own recovery programme actually achieves, or a deliberately pessimistic figure if you are building a business case. And note one further conservatism: abandoned carts typically hold less value on average than completed orders, so pricing them at completed-order AOV tilts the ceiling upward before you have even started.

What is cart abandonment rate calculator?

Cart abandonment rate is one minus the share of created carts that end in a purchase, expressed as a percentage. Checkout abandonment rate is the same idea measured from a narrower base — only the shoppers who actually entered the checkout flow. Both are legitimate; they simply answer different questions, and the checkout figure is always the lower of the two because everyone counted in it has already demonstrated more intent. A third rate sits between them: the share of carts that reach checkout at all. Together the three describe a two-stage funnel, and multiplying the two stage survival rates reproduces the overall cart-to-purchase rate exactly. Baymard Institute's published average of documented rates, 70.22% across 50 studies, is a cart-level figure.

How to use this calculator.

1. 01Pull all three counts from the same report and the same date range. Carts created, checkouts started and purchases completed must describe one funnel; mixing a monthly order count with a weekly cart count is the fastest way to a nonsense rate.
2. 02Count carts, not items. A cart with four products in it is one cart, however many add_to_cart events it fired.
3. 03Exclude orders that never had a cart — phone orders, in-store sales, manual invoices. They inflate the numerator without ever entering the denominator.
4. 04Add an average order value only if you want the money figures. If you can get the average value of abandoned carts specifically, use that instead: it is usually lower than completed-order AOV, and using the higher figure overstates the ceiling.
5. 05Set the recovery rate to something you can defend. It is your assumption, not a benchmark, and it drives the last output entirely.
6. 06Read the two abandonment rates together and check which stage lost more shoppers in absolute terms. A high checkout abandonment rate on a tiny checkout population is a much smaller problem than a mediocre one on a large population.

The formula.

Cart abandonment rate = (1 − purchases ÷ carts created) × 100. Checkout abandonment rate = (1 − purchases ÷ checkouts started) × 100. Cart-to-checkout rate = checkouts started ÷ carts created × 100. With the worked figures: 1 − 1,450 ÷ 10,000 = 0.855, so 85.50%; 1 − 1,450 ÷ 4,200 = 0.654761904…, so 65.4762%; and 4,200 ÷ 10,000 = 42.00%.

The three are not independent. Cart survival equals the product of the two stage survivals: 0.42 × (1 − 0.654761904…) = 0.42 × 0.345238095… = 0.145, which is exactly the 14.50% of carts that converted, and 1 − 0.145 = 0.855. That identity is a useful sanity check on your data; if it does not hold, your three counts are not describing the same funnel.

The money side is two multiplications. Abandoned carts = carts created − purchases = 10,000 − 1,450 = 8,550. Value in abandoned carts = 8,550 × $92.00 = $786,600.00. Recoverable at the rate you supply = $786,600.00 × 10% = $78,660.00. Neither figure has any authority beyond the assumptions you fed it, which is why the recovery rate is an editable input and the page prints the ceiling caveat beside the result.

Rounding stage: nothing is rounded on the way through. All three rates, the counts and both currency figures stay at full decimal precision and are rounded once, at the point results are returned, to ten decimal places. The only earlier rounding is inside the plain-language "where the carts went" sentence, which formats counts as whole numbers and money to two decimals so it reads like English; every numeric output above it is unrounded.

A worked example.

Frequently asked questions.

References& sources.

1. [1]Baymard Institute, "50 Cart Abandonment Rate Statistics" (current edition, most recent underlying study retrieved by Baymard in August 2025; page retrieved by us 2026-07-29). Source of the headline context figure — "70.22 % – average documented online shopping cart abandonment rate … an average calculated based on 50 different studies" — and of the reasons data: "our latest quantitative study of reasons for abandonment found that 42% of US online shoppers have abandoned a cart because 'I was just browsing / not ready to buy'", followed by extra costs too high 40%, delivery too slow 20%, card-security distrust 19% and forced account creation 18%. Independent research institute publishing both its own study and a documented meta-average of others; the underlying studies are individually listed with dates and disagree with one another by roughly ten percentage points. Publicly accessible.
2. [2]Google, "GA4 recommended events" developer reference (current edition, retrieved 2026-07-29). Defines the three funnel stages this calculator uses: add_to_cart — "This event signifies that an item was added to a cart for purchase"; begin_checkout — "This event signifies that a user has begun a checkout"; purchase — "This event signifies when one or more items is purchased by a user". Consulted as an independent second authority on where the funnel boundaries sit; it agrees with Baymard's cart-versus-checkout distinction and supplies the event names to pull the counts from. Publicly accessible.
3. [3]Kukar-Kinney, M. & Close, A. G. (2010). "The determinants of consumers' online shopping cart abandonment." Journal of the Academy of Marketing Science, 38(2), 240–250, DOI 10.1007/s11747-009-0141-5. The foundational peer-reviewed study of why online carts are abandoned, including the finding that carts are widely used for purposes other than immediate purchase. Bibliographic record verified against Crossref 2026-07-29 (authors, journal, volume, issue, pages, DOI all confirmed); the abstract and full text are paywalled and were not retrieved, so no verbatim figure is attributed to it here — the 42% browsing figure used on this page comes from Baymard above.
4. [4]Kukar-Kinney, M., Scheinbaum, A. C., Orimoloye, L. O., Carlson, J. R. & He, H. (2022). "A model of online shopping cart abandonment: evidence from e-tail clickstream data." Journal of the Academy of Marketing Science, 50(5), 961–980, DOI 10.1007/s11747-022-00857-8. The modern clickstream successor to the 2010 study, offered as further reading on abandonment behaviour. Bibliographic record verified against Crossref 2026-07-29; full text paywalled and not retrieved, so no figure is attributed to it.