Group name
Website heatmap
Webflow Optimize
Webflow A/B testing
Voice of customer
User journey map
User behavior analytics
Usability testing
Trust signals
Tree testing
Time on page
Survey design
Statistical significance
Split URL testing
Split testing
Social proof
Session replay
Session replay tools
Session recording
Sequential testing
Segmentation analysis
Scroll map
Scroll depth
Scarcity marketing
Revenue per visitor
Rage click
PIE framework
Novelty effect
Multivariate testing
Mobile conversion rate
Microsoft Clarity
Micro conversion
Message match
Macro conversion
LIFT model
Landing page optimization
Landing page conversion rate
Information scent
ICE score
Hotjar
Holdout group
Hick's law
Heatmap tools
Guardrail metrics
Goal completion
Funnel analysis
Form analytics
Form abandonment
Five second test
Fitts's law
Exit rate
Exit intent popup
Event tracking
Drop-off rate
Dead click
CRO tools
CRO audit
Choosing CRO tools
Conversion funnel
Cohort analysis
Cognitive load
Click map
Checkout optimization
Cart abandonment
Bounce rate
Bayesian A/B testing
Average order value
Attention map
Anchoring bias
Above the fold
A/B testing tools
What is cart abandonment?
Cart abandonment is when a shopper adds items to a cart and leaves without completing the purchase. It is measured as the share of created carts that produce no order, and the documented average across published studies sits near 70%, which makes it the largest single revenue leak in ecommerce.
What is the average cart abandonment rate?
Baymard Institute maintains an aggregate across published studies and reports an average around 70.2%. Baymard revises that aggregate as it adds studies, so quote it with the date you checked.
Treat that figure as a reference point rather than a target. Abandonment varies enormously by vertical, price point, and device, and a rate below the average is not automatically good. A store with an unusually low rate may be failing to attract browsers rather than converting them well.
Two measurement notes that change the number more than most optimizations do:
Cart creation definition. Counting a cart when the first item is added produces a much higher rate than counting when checkout begins. Compare like for like.
Browsing behavior. A meaningful share of carts are used as wishlists or price comparison tools by people who never intended to buy on that visit. That portion is not recoverable, and treating it as a failure inflates the perceived opportunity.
Why do shoppers abandon carts?
These are the reasons shoppers give when surveyed, ordered as they usually appear. Self-reported reasons are directional rather than exact, since people rationalize a decision after making it, and the ranking is still stable enough to plan against.
Unexpected extra costs. Shipping, taxes, and fees revealed at checkout. The dominant cause across studies, and the most fixable, since the fix is disclosure timing rather than price.
Forced account creation. Requiring registration before purchase. It ranks high because it demands commitment before the shopper has received anything, and guest checkout removes it entirely.
A long or complicated checkout. Nearly 1 in 5 shoppers report abandoning for this reason, against an average US checkout displaying 23.48 form elements where roughly 12 to 14 is the documented ideal. Most checkouts could remove 20 to 60% of displayed elements.
Trust concerns at payment. No recognizable payment marks, an unfamiliar processor, or a page that looks different from the rest of the store.
Delivery uncertainty. No stated delivery date, or one that arrives too late.
Errors and crashes. Rarer, and total when they occur.
Most abandonment traces to something the checkout revealed rather than to a change of mind about the product, which is why disclosure and flow changes return more than persuasion does.
The same mechanism runs outside ecommerce. A B2B SaaS trial that asks for a card at step one, a plan page that hides seat minimums until checkout, or a self-serve signup that ends in a mandatory sales call each reveal a cost late, and they lose people for the reason a surprise shipping charge does.
Which recovery tactics work?
Ordered by expected return, which runs close to the inverse of how heavily each is sold.
- Show total cost early. Shipping and tax visible on the product or cart page removes the surprise that causes the largest share of abandonment.
- Offer guest checkout. Account creation after purchase, never before.
- Cut form fields. See form abandonment for the field-level method.
- Abandonment emails. A short sequence, first message within an hour. Effective, and it treats the symptom rather than the cause.
- Persistent carts across devices and sessions.
- Exit-intent offers. Modest returns and a real risk of training shoppers to abandon in order to trigger a discount. See exit intent popup.
How does this apply to Webflow Ecommerce?
Webflow Ecommerce builds checkout from a fixed set of components rather than a freely editable page, so the field-level surgery in the causes list has a lower ceiling here than on a custom stack. Disclosure timing stays fully available, and it is the higher-return fix anyway. Shipping and tax resolve at the checkout step, so stating rates and free-shipping thresholds on the product and cart pages is content you control rather than a platform setting you wait for.
Related terms
Form abandonment · Checkout optimization · Conversion funnel · Average order value · Exit intent popup
Service: Conversion Rate Optimization.
FAQ
What is a good cart abandonment rate?
Below the roughly 70% documented average is a reasonable reference, and the more useful comparison is against your own history and your own vertical. A very low rate can indicate weak top-of-funnel traffic rather than strong checkout performance.
Is cart abandonment the same as checkout abandonment?
No. Cart abandonment covers everyone who added an item and did not buy. Checkout abandonment covers the narrower group who began checkout and did not finish. Checkout abandonment rates are lower because that group has stronger intent.
Do abandonment emails work?
They recover a share of otherwise lost orders, with one constraint that sets the ceiling: you can only email a cart whose owner you have already identified. On a store where most people check out as guests, the addressable population is a minority of abandoned carts, while a fix inside checkout reaches all of them.