Post-conversion page experiments including upsells, referrals, and next-step optimization.
Across 5 thank you page experiments, 40% resulted in a statistically significant win. Winning variants saw an average lift of +6.3%.
3 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 thank you page testing strategy and avoid repeating experiments that have already been run.
Context: Visual elements on the thank you aren't doing enough to communicate value, build trust, or guide users toward the next step.
Context: Friction during the confirmation page process causes users to abandon right when they're closest to converting.
Context: The first screen of the order-confirmation must immediately communicate value — if it doesn't, users bounce before scrolling.
Problem: Each additional form field adds friction to the thank you, increasing the chance users abandon before completing their submission.
Problem: Coupon and promo code fields on thank yous can distract users — they leave to hunt for codes, reducing completion rates.
Save your own experiments, get AI-powered test ideas, and build on patterns from 5+ real tests.
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