A/B tests from e-commerce companies including product pages, checkout flows, and conversion optimization patterns.
Across 113 e-commerce experiments, 53% resulted in a statistically significant win. Winning variants saw an average lift of +37.0%. Meanwhile, 15 tests underperformed the control.
38 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 e-commerce testing strategy and avoid repeating experiments that have already been run.
Problem: Visual elements on the product aren't doing enough to communicate value, build trust, or guide users toward the next step.
Problem: Users on the listing need validation from others before committing — without visible proof of success, they hesitate.
Problem: The information hierarchy on the product may not match how users actually scan and process the content.
Problem: Users on the product don't feel confident enough to proceed — they need reassurance that their data and money are safe.
Problem: The primary call-to-action on the product isn't converting at its potential — design, copy, or placement may be the bottleneck.
Problem: The information hierarchy on the product may not match how users actually scan and process the content.
Problem: Users on the product need validation from others before committing — without visible proof of success, they hesitate.
Problem: Users arriving at the product can't efficiently find what they're looking for, increasing bounce rates.
Problem: The primary call-to-action on the general isn't converting at its potential — design, copy, or placement may be the bottleneck.
Problem: Users arriving at the product can't efficiently find what they're looking for, increasing bounce rates.
Problem: The primary call-to-action on the general isn't converting at its potential — design, copy, or placement may be the bottleneck.
Problem: How "Ux pattern optimization" is implemented on the home landing can meaningfully affect conversion — this element is worth testing.
Problem: Key actions on the product disappear as users scroll, creating a gap between intent and the ability to act.
Problem: The primary call-to-action on the product isn't converting at its potential — design, copy, or placement may be the bottleneck.
Problem: Users arriving at the product can't efficiently find what they're looking for, increasing bounce rates.
Problem: Users arriving at the general can't efficiently find what they're looking for, increasing bounce rates.
Problem: Key actions on the product disappear as users scroll, creating a gap between intent and the ability to act.
Problem: How "Listing page" is implemented on the listing can meaningfully affect conversion — this element is worth testing.
Problem: Visual emphasis on the product may not be drawing attention to the right elements — size, color, and contrast guide the eye.
Problem: The primary call-to-action on the product isn't converting at its potential — design, copy, or placement may be the bottleneck.
Problem: The information hierarchy on the product may not match how users actually scan and process the content.
Problem: Users on the product need validation from others before committing — without visible proof of success, they hesitate.
Problem: How prices are displayed on the product directly influences perceived value and willingness to buy.
Problem: The primary call-to-action on the product isn't converting at its potential — design, copy, or placement may be the bottleneck.
Problem: Users on the product need validation from others before committing — without visible proof of success, they hesitate.
Problem: Visual elements on the product aren't doing enough to communicate value, build trust, or guide users toward the next step.
Problem: The information hierarchy on the listing may not match how users actually scan and process the content.
Problem: Friction during the product process causes users to abandon right when they're closest to converting.
Problem: The information hierarchy on the listing may not match how users actually scan and process the content.
Problem: Users can't quickly find relevant products or content on the listing, leading to frustration and early exits.
Save your own experiments, get AI-powered test ideas, and build on patterns from 113+ real tests.
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