Mobile: Mobile Grid Page Filters
Test Results
Key Learning
Context: Mobile users experience the mobile differently — smaller screens, touch targets, and limited attention require purpose-built design.
What was tested: A variation was tested against the existing experience.
Result: No statistically significant difference was detected. No significant difference suggests users adapted to the change quickly, or the variation didn't address the actual friction point. Try testing more targeted elements.
How to Apply This to Your Site
This experiment tested mobile: mobile grid page filters but produced no statistically significant change. The test was run on a mobile page in the energy & utilities 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 large sample sizes to detect small effects. This test ran for 50 days — plan for at least that long.
This result reached 95% statistical confidence, meaning there is a very low probability the observed effect was due to chance. Results at this confidence level are generally considered reliable for making business decisions.
What Was Tested
A/B test on mobile testing layout changes.
Methodology
Build On These Learnings
Save your own experiments, spot winning patterns across your test history, and stop repeating what's already been tried.
Related Experiments
Restructuring Homepage Hierarchy to Surface Personalized Offers
The story behind this win is the iteration discipline. The first attempt at this homepage redesign changed two systems at once (messaging + routing) and produced an ambiguous result: the entry metric moved slightly positive while downstream metrics moved meaningfully negative. The team correctly identified that the routing change — which inadvertently replaced direct links to a personalized plan-search experience with modal-driven entry into a generic flow — was the downstream killer. The iteration restored the original routing and kept ONLY the homepage hierarchy changes. All funnel metrics moved directionally positive in lockstep (entry +2.38%, mid-funnel +7%, conversion +11.81%) — none stat-sig individually but consistent enough across the funnel to justify shipping. Element-level diagnostics confirmed the mechanism: the segment CTAs the team intended to promote saw a 26-30% lift in unique-visitor interaction, while the unchanged hero banner stayed flat (as expected). Two key behavioral observations: (1) page-length reduction surfaced a 4x lift on a previously buried bottom-of-page zip code input — proving the secondary lesson that 'less page' can mean 'more conversion real estate'; (2) desktop strongly outperformed mobile, with the suspected cause being mobile's lead-with-form pattern (zip code above hero) — putting the form before the message creates friction. The broader transferable insight: when a messy test confounds multiple variables, the right move is to isolate one variable in the next test, not to abandon the hypothesis.
Does Restructuring Plan Detail Cards Improve Click-Through?
Test the variable users actually complain about — not the variable that's easiest to redesign. This test is a textbook case of treating form when the problem is content. Cross-brand qualitative research had consistently flagged three specific confusion themes: (1) pricing structure is opaque — users can't predict what they'll pay; (2) plan names are brand-driven rather than benefit-driven, so the names themselves don't communicate what the user is buying; (3) no side-by-side comparison — vertical layouts force users to scroll and remember instead of compare in parallel. Visual hierarchy is a presentation improvement; it does nothing about pricing opacity, naming clarity, or comparison difficulty. The test reached its planned sample size and produced a directionally-negative result at the noise floor — because organizing unclear content doesn't make the content clearer. The transferable insight isn't about visual hierarchy specifically; it's about the importance of mapping qualitative complaints to the test variable. If the user research says 'I don't understand what this plan costs,' the test should manipulate cost-clarity. If it says 'I can't tell these plans apart,' the test should manipulate differentiation. Layout tests are appropriate when the complaint is about layout — not when they're a default reflex.
Content Page: Maybe Later on Content Page
Context: Key actions on the content page disappear as users scroll, creating a gap between intent and the ability to act.
Checkout: Multiple Steps
Problem: Friction during the checkout process causes users to abandon right when they're closest to converting.