Baymard's published research gives ecommerce teams a starting point: the documented average cart abandonment rate is 70.22%. The more useful question is where friction appears between cart and order. A single sitewide rate cannot answer that.
Checkout friction scorecard
| Check | Evidence to collect | Operating decision |
|---|---|---|
| Delivery cost | Cost shown before payment | Test earlier disclosure if late fees cause exits |
| Account requirement | Guest path and account prompts | Remove forced registration from first purchase |
| Form usability | Error rate and correction time | Simplify fields and preserve entered values |
| Payment reliability | Failure rate by method and device | Route failures to a monitored queue |
| Mobile behavior | Completion by viewport and browser | Reproduce the worst mobile path |
Source: Baymard UX statistics and checkout flow guidance, accessed August 3, 2026. Baymard's evidence combines moderated usability research, benchmarking, and quantitative studies, so it should guide hypotheses rather than promise a fixed lift.
A practical review sequence
Pull four weeks of checkout events and calculate completion at cart, shipping, payment, and order confirmation. Keep the event definition stable. Then compare the worst segment with the median segment. A payment issue limited to one browser needs a different owner from high shipping costs affecting every device.
Use session recordings or test orders only after analytics shows where to look. Record the exact error message, the field that caused it, and whether the customer can recover. Put each issue into a table with an owner, expected impact, evidence, and a retest date.
The marketing dashboard setup guide covers the reporting layer. Pair it with the paid ads reporting guide when traffic source quality may be part of the problem.
Frequently asked questions
What is the most useful checkout benchmark?
Step completion by device and source is more actionable than a single cart abandonment average.
How do I prioritize checkout fixes?
Start with the largest revenue-weighted loss that customers can realistically recover from. Confirm it with a test order and a follow-up measurement window.
Should I redesign the whole checkout?
Usually not as a first move. Identify one measurable friction point and test the smallest change that addresses it.
Related research
If the review queue needs a consistent owner, marketing analytics VA support can maintain event checks and evidence logs.
Sources
- Baymard, 40+ UX Statistics, accessed August 3, 2026: https://baymard.com/learn/ux-statistics
- Baymard, Checkout Flow UX Optimization, accessed August 3, 2026: https://baymard.com/learn/checkout-flow-ux-optimization