Multiple: UX Optimization
Hypothesis
Site UX improvements for will improve overall conversion while also improving the quality of traffic by converting more first-time buyers (new customers).
Test Results
Key Learning
Context: Users arriving at the multiple can't efficiently find what they're looking for, increasing bounce rates.
What was tested: CVR improvements that hold during ad spend increases are more reliable indicators of genuine site improvement. 25% new customer growth while doubling ad spend suggests improved landing page quality scores and conversion efficiency. Home goods brands with strong emotional product stories (comfort, family) convert better when UX surfaces that story. New customer acquisition rate is a more meaningful metric than overall CVR when scaling paid acquisition
Result: No statistically significant difference was detected. This null result is still valuable — it narrows the search space and helps calibrate your minimum detectable effect for future tests.
How to Apply This to Your Site
This experiment tested multiple: ux optimization but produced no statistically significant change. The test was run on a landing page page in the e-commerce industry. Inconclusive results suggest this particular change may not be a priority — focus testing effort on higher-impact areas.
Before you test: Consider that layout tests typically require adequate traffic to reach statistical significance. Run your test for at least 2 full business cycles to account for weekly traffic patterns.
What Was Tested
a home goods brand (likely inflatable furniture/play), worked with Oddit for a site UX audit. Post-implementation, CVR increased 40% and new customer acquisition increased 25% alongside a doubling of ad spend. The new customer growth during a period of increased ad spend suggests the UX improvements made paid acquisition more efficient
Methodology
Build On These Learnings
Save your own experiments, spot winning patterns across your test history, and stop repeating what's already been tried.
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