Shopping cart experiments including upsells, urgency, and friction reduction patterns.
Across 5 cart experiments, 20% resulted in a statistically significant win. Winning variants saw an average lift of +8.5%.
4 experiments were inconclusive, meaning the difference between control and variant was not statistically significant. Inconclusive results are still valuable — they tell you what doesn't move the needle, so you can focus testing effort elsewhere.
These results come from real A/B tests with sample sizes ranging from hundreds to millions of visitors. Use them to inform your own cart testing strategy and avoid repeating experiments that have already been run.
Context: How prices are displayed on the shopping cart directly influences perceived value and willingness to buy.
Context: Friction during the shopping cart process causes users to abandon right when they're closest to converting.
Context: The primary call-to-action on the cart isn't converting at its potential — design, copy, or placement may be the bottleneck.
Problem: How prices are displayed on the shopping cart directly influences perceived value and willingness to buy.
Context: Mobile users experience the cart differently — smaller screens, touch targets, and limited attention require purpose-built design.
Save your own experiments, get AI-powered test ideas, and build on patterns from 5+ real tests.
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